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Omer Karisman
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Parent(s):
Omni Zero Couples
Browse files- .dockerignore +1 -0
- .gitignore +5 -0
- LICENSE +674 -0
- README.md +39 -0
- app.py +147 -0
- cog.yaml +29 -0
- demo.py +39 -0
- omni_zero.py +229 -0
- pipeline.py +0 -0
- predict.py +70 -0
- requirements.txt +22 -0
- utils.py +168 -0
.dockerignore
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models
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.gitignore
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__pycache__
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models
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.cog/*
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.cog
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venv
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LICENSE
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GNU GENERAL PUBLIC LICENSE
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Version 3, 29 June 2007
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Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
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|
175 |
+
Conveying under any other circumstances is permitted solely under
|
176 |
+
the conditions stated below. Sublicensing is not allowed; section 10
|
177 |
+
makes it unnecessary.
|
178 |
+
|
179 |
+
3. Protecting Users' Legal Rights From Anti-Circumvention Law.
|
180 |
+
|
181 |
+
No covered work shall be deemed part of an effective technological
|
182 |
+
measure under any applicable law fulfilling obligations under article
|
183 |
+
11 of the WIPO copyright treaty adopted on 20 December 1996, or
|
184 |
+
similar laws prohibiting or restricting circumvention of such
|
185 |
+
measures.
|
186 |
+
|
187 |
+
When you convey a covered work, you waive any legal power to forbid
|
188 |
+
circumvention of technological measures to the extent such circumvention
|
189 |
+
is effected by exercising rights under this License with respect to
|
190 |
+
the covered work, and you disclaim any intention to limit operation or
|
191 |
+
modification of the work as a means of enforcing, against the work's
|
192 |
+
users, your or third parties' legal rights to forbid circumvention of
|
193 |
+
technological measures.
|
194 |
+
|
195 |
+
4. Conveying Verbatim Copies.
|
196 |
+
|
197 |
+
You may convey verbatim copies of the Program's source code as you
|
198 |
+
receive it, in any medium, provided that you conspicuously and
|
199 |
+
appropriately publish on each copy an appropriate copyright notice;
|
200 |
+
keep intact all notices stating that this License and any
|
201 |
+
non-permissive terms added in accord with section 7 apply to the code;
|
202 |
+
keep intact all notices of the absence of any warranty; and give all
|
203 |
+
recipients a copy of this License along with the Program.
|
204 |
+
|
205 |
+
You may charge any price or no price for each copy that you convey,
|
206 |
+
and you may offer support or warranty protection for a fee.
|
207 |
+
|
208 |
+
5. Conveying Modified Source Versions.
|
209 |
+
|
210 |
+
You may convey a work based on the Program, or the modifications to
|
211 |
+
produce it from the Program, in the form of source code under the
|
212 |
+
terms of section 4, provided that you also meet all of these conditions:
|
213 |
+
|
214 |
+
a) The work must carry prominent notices stating that you modified
|
215 |
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it, and giving a relevant date.
|
216 |
+
|
217 |
+
b) The work must carry prominent notices stating that it is
|
218 |
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released under this License and any conditions added under section
|
219 |
+
7. This requirement modifies the requirement in section 4 to
|
220 |
+
"keep intact all notices".
|
221 |
+
|
222 |
+
c) You must license the entire work, as a whole, under this
|
223 |
+
License to anyone who comes into possession of a copy. This
|
224 |
+
License will therefore apply, along with any applicable section 7
|
225 |
+
additional terms, to the whole of the work, and all its parts,
|
226 |
+
regardless of how they are packaged. This License gives no
|
227 |
+
permission to license the work in any other way, but it does not
|
228 |
+
invalidate such permission if you have separately received it.
|
229 |
+
|
230 |
+
d) If the work has interactive user interfaces, each must display
|
231 |
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Appropriate Legal Notices; however, if the Program has interactive
|
232 |
+
interfaces that do not display Appropriate Legal Notices, your
|
233 |
+
work need not make them do so.
|
234 |
+
|
235 |
+
A compilation of a covered work with other separate and independent
|
236 |
+
works, which are not by their nature extensions of the covered work,
|
237 |
+
and which are not combined with it such as to form a larger program,
|
238 |
+
in or on a volume of a storage or distribution medium, is called an
|
239 |
+
"aggregate" if the compilation and its resulting copyright are not
|
240 |
+
used to limit the access or legal rights of the compilation's users
|
241 |
+
beyond what the individual works permit. Inclusion of a covered work
|
242 |
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in an aggregate does not cause this License to apply to the other
|
243 |
+
parts of the aggregate.
|
244 |
+
|
245 |
+
6. Conveying Non-Source Forms.
|
246 |
+
|
247 |
+
You may convey a covered work in object code form under the terms
|
248 |
+
of sections 4 and 5, provided that you also convey the
|
249 |
+
machine-readable Corresponding Source under the terms of this License,
|
250 |
+
in one of these ways:
|
251 |
+
|
252 |
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a) Convey the object code in, or embodied in, a physical product
|
253 |
+
(including a physical distribution medium), accompanied by the
|
254 |
+
Corresponding Source fixed on a durable physical medium
|
255 |
+
customarily used for software interchange.
|
256 |
+
|
257 |
+
b) Convey the object code in, or embodied in, a physical product
|
258 |
+
(including a physical distribution medium), accompanied by a
|
259 |
+
written offer, valid for at least three years and valid for as
|
260 |
+
long as you offer spare parts or customer support for that product
|
261 |
+
model, to give anyone who possesses the object code either (1) a
|
262 |
+
copy of the Corresponding Source for all the software in the
|
263 |
+
product that is covered by this License, on a durable physical
|
264 |
+
medium customarily used for software interchange, for a price no
|
265 |
+
more than your reasonable cost of physically performing this
|
266 |
+
conveying of source, or (2) access to copy the
|
267 |
+
Corresponding Source from a network server at no charge.
|
268 |
+
|
269 |
+
c) Convey individual copies of the object code with a copy of the
|
270 |
+
written offer to provide the Corresponding Source. This
|
271 |
+
alternative is allowed only occasionally and noncommercially, and
|
272 |
+
only if you received the object code with such an offer, in accord
|
273 |
+
with subsection 6b.
|
274 |
+
|
275 |
+
d) Convey the object code by offering access from a designated
|
276 |
+
place (gratis or for a charge), and offer equivalent access to the
|
277 |
+
Corresponding Source in the same way through the same place at no
|
278 |
+
further charge. You need not require recipients to copy the
|
279 |
+
Corresponding Source along with the object code. If the place to
|
280 |
+
copy the object code is a network server, the Corresponding Source
|
281 |
+
may be on a different server (operated by you or a third party)
|
282 |
+
that supports equivalent copying facilities, provided you maintain
|
283 |
+
clear directions next to the object code saying where to find the
|
284 |
+
Corresponding Source. Regardless of what server hosts the
|
285 |
+
Corresponding Source, you remain obligated to ensure that it is
|
286 |
+
available for as long as needed to satisfy these requirements.
|
287 |
+
|
288 |
+
e) Convey the object code using peer-to-peer transmission, provided
|
289 |
+
you inform other peers where the object code and Corresponding
|
290 |
+
Source of the work are being offered to the general public at no
|
291 |
+
charge under subsection 6d.
|
292 |
+
|
293 |
+
A separable portion of the object code, whose source code is excluded
|
294 |
+
from the Corresponding Source as a System Library, need not be
|
295 |
+
included in conveying the object code work.
|
296 |
+
|
297 |
+
A "User Product" is either (1) a "consumer product", which means any
|
298 |
+
tangible personal property which is normally used for personal, family,
|
299 |
+
or household purposes, or (2) anything designed or sold for incorporation
|
300 |
+
into a dwelling. In determining whether a product is a consumer product,
|
301 |
+
doubtful cases shall be resolved in favor of coverage. For a particular
|
302 |
+
product received by a particular user, "normally used" refers to a
|
303 |
+
typical or common use of that class of product, regardless of the status
|
304 |
+
of the particular user or of the way in which the particular user
|
305 |
+
actually uses, or expects or is expected to use, the product. A product
|
306 |
+
is a consumer product regardless of whether the product has substantial
|
307 |
+
commercial, industrial or non-consumer uses, unless such uses represent
|
308 |
+
the only significant mode of use of the product.
|
309 |
+
|
310 |
+
"Installation Information" for a User Product means any methods,
|
311 |
+
procedures, authorization keys, or other information required to install
|
312 |
+
and execute modified versions of a covered work in that User Product from
|
313 |
+
a modified version of its Corresponding Source. The information must
|
314 |
+
suffice to ensure that the continued functioning of the modified object
|
315 |
+
code is in no case prevented or interfered with solely because
|
316 |
+
modification has been made.
|
317 |
+
|
318 |
+
If you convey an object code work under this section in, or with, or
|
319 |
+
specifically for use in, a User Product, and the conveying occurs as
|
320 |
+
part of a transaction in which the right of possession and use of the
|
321 |
+
User Product is transferred to the recipient in perpetuity or for a
|
322 |
+
fixed term (regardless of how the transaction is characterized), the
|
323 |
+
Corresponding Source conveyed under this section must be accompanied
|
324 |
+
by the Installation Information. But this requirement does not apply
|
325 |
+
if neither you nor any third party retains the ability to install
|
326 |
+
modified object code on the User Product (for example, the work has
|
327 |
+
been installed in ROM).
|
328 |
+
|
329 |
+
The requirement to provide Installation Information does not include a
|
330 |
+
requirement to continue to provide support service, warranty, or updates
|
331 |
+
for a work that has been modified or installed by the recipient, or for
|
332 |
+
the User Product in which it has been modified or installed. Access to a
|
333 |
+
network may be denied when the modification itself materially and
|
334 |
+
adversely affects the operation of the network or violates the rules and
|
335 |
+
protocols for communication across the network.
|
336 |
+
|
337 |
+
Corresponding Source conveyed, and Installation Information provided,
|
338 |
+
in accord with this section must be in a format that is publicly
|
339 |
+
documented (and with an implementation available to the public in
|
340 |
+
source code form), and must require no special password or key for
|
341 |
+
unpacking, reading or copying.
|
342 |
+
|
343 |
+
7. Additional Terms.
|
344 |
+
|
345 |
+
"Additional permissions" are terms that supplement the terms of this
|
346 |
+
License by making exceptions from one or more of its conditions.
|
347 |
+
Additional permissions that are applicable to the entire Program shall
|
348 |
+
be treated as though they were included in this License, to the extent
|
349 |
+
that they are valid under applicable law. If additional permissions
|
350 |
+
apply only to part of the Program, that part may be used separately
|
351 |
+
under those permissions, but the entire Program remains governed by
|
352 |
+
this License without regard to the additional permissions.
|
353 |
+
|
354 |
+
When you convey a copy of a covered work, you may at your option
|
355 |
+
remove any additional permissions from that copy, or from any part of
|
356 |
+
it. (Additional permissions may be written to require their own
|
357 |
+
removal in certain cases when you modify the work.) You may place
|
358 |
+
additional permissions on material, added by you to a covered work,
|
359 |
+
for which you have or can give appropriate copyright permission.
|
360 |
+
|
361 |
+
Notwithstanding any other provision of this License, for material you
|
362 |
+
add to a covered work, you may (if authorized by the copyright holders of
|
363 |
+
that material) supplement the terms of this License with terms:
|
364 |
+
|
365 |
+
a) Disclaiming warranty or limiting liability differently from the
|
366 |
+
terms of sections 15 and 16 of this License; or
|
367 |
+
|
368 |
+
b) Requiring preservation of specified reasonable legal notices or
|
369 |
+
author attributions in that material or in the Appropriate Legal
|
370 |
+
Notices displayed by works containing it; or
|
371 |
+
|
372 |
+
c) Prohibiting misrepresentation of the origin of that material, or
|
373 |
+
requiring that modified versions of such material be marked in
|
374 |
+
reasonable ways as different from the original version; or
|
375 |
+
|
376 |
+
d) Limiting the use for publicity purposes of names of licensors or
|
377 |
+
authors of the material; or
|
378 |
+
|
379 |
+
e) Declining to grant rights under trademark law for use of some
|
380 |
+
trade names, trademarks, or service marks; or
|
381 |
+
|
382 |
+
f) Requiring indemnification of licensors and authors of that
|
383 |
+
material by anyone who conveys the material (or modified versions of
|
384 |
+
it) with contractual assumptions of liability to the recipient, for
|
385 |
+
any liability that these contractual assumptions directly impose on
|
386 |
+
those licensors and authors.
|
387 |
+
|
388 |
+
All other non-permissive additional terms are considered "further
|
389 |
+
restrictions" within the meaning of section 10. If the Program as you
|
390 |
+
received it, or any part of it, contains a notice stating that it is
|
391 |
+
governed by this License along with a term that is a further
|
392 |
+
restriction, you may remove that term. If a license document contains
|
393 |
+
a further restriction but permits relicensing or conveying under this
|
394 |
+
License, you may add to a covered work material governed by the terms
|
395 |
+
of that license document, provided that the further restriction does
|
396 |
+
not survive such relicensing or conveying.
|
397 |
+
|
398 |
+
If you add terms to a covered work in accord with this section, you
|
399 |
+
must place, in the relevant source files, a statement of the
|
400 |
+
additional terms that apply to those files, or a notice indicating
|
401 |
+
where to find the applicable terms.
|
402 |
+
|
403 |
+
Additional terms, permissive or non-permissive, may be stated in the
|
404 |
+
form of a separately written license, or stated as exceptions;
|
405 |
+
the above requirements apply either way.
|
406 |
+
|
407 |
+
8. Termination.
|
408 |
+
|
409 |
+
You may not propagate or modify a covered work except as expressly
|
410 |
+
provided under this License. Any attempt otherwise to propagate or
|
411 |
+
modify it is void, and will automatically terminate your rights under
|
412 |
+
this License (including any patent licenses granted under the third
|
413 |
+
paragraph of section 11).
|
414 |
+
|
415 |
+
However, if you cease all violation of this License, then your
|
416 |
+
license from a particular copyright holder is reinstated (a)
|
417 |
+
provisionally, unless and until the copyright holder explicitly and
|
418 |
+
finally terminates your license, and (b) permanently, if the copyright
|
419 |
+
holder fails to notify you of the violation by some reasonable means
|
420 |
+
prior to 60 days after the cessation.
|
421 |
+
|
422 |
+
Moreover, your license from a particular copyright holder is
|
423 |
+
reinstated permanently if the copyright holder notifies you of the
|
424 |
+
violation by some reasonable means, this is the first time you have
|
425 |
+
received notice of violation of this License (for any work) from that
|
426 |
+
copyright holder, and you cure the violation prior to 30 days after
|
427 |
+
your receipt of the notice.
|
428 |
+
|
429 |
+
Termination of your rights under this section does not terminate the
|
430 |
+
licenses of parties who have received copies or rights from you under
|
431 |
+
this License. If your rights have been terminated and not permanently
|
432 |
+
reinstated, you do not qualify to receive new licenses for the same
|
433 |
+
material under section 10.
|
434 |
+
|
435 |
+
9. Acceptance Not Required for Having Copies.
|
436 |
+
|
437 |
+
You are not required to accept this License in order to receive or
|
438 |
+
run a copy of the Program. Ancillary propagation of a covered work
|
439 |
+
occurring solely as a consequence of using peer-to-peer transmission
|
440 |
+
to receive a copy likewise does not require acceptance. However,
|
441 |
+
nothing other than this License grants you permission to propagate or
|
442 |
+
modify any covered work. These actions infringe copyright if you do
|
443 |
+
not accept this License. Therefore, by modifying or propagating a
|
444 |
+
covered work, you indicate your acceptance of this License to do so.
|
445 |
+
|
446 |
+
10. Automatic Licensing of Downstream Recipients.
|
447 |
+
|
448 |
+
Each time you convey a covered work, the recipient automatically
|
449 |
+
receives a license from the original licensors, to run, modify and
|
450 |
+
propagate that work, subject to this License. You are not responsible
|
451 |
+
for enforcing compliance by third parties with this License.
|
452 |
+
|
453 |
+
An "entity transaction" is a transaction transferring control of an
|
454 |
+
organization, or substantially all assets of one, or subdividing an
|
455 |
+
organization, or merging organizations. If propagation of a covered
|
456 |
+
work results from an entity transaction, each party to that
|
457 |
+
transaction who receives a copy of the work also receives whatever
|
458 |
+
licenses to the work the party's predecessor in interest had or could
|
459 |
+
give under the previous paragraph, plus a right to possession of the
|
460 |
+
Corresponding Source of the work from the predecessor in interest, if
|
461 |
+
the predecessor has it or can get it with reasonable efforts.
|
462 |
+
|
463 |
+
You may not impose any further restrictions on the exercise of the
|
464 |
+
rights granted or affirmed under this License. For example, you may
|
465 |
+
not impose a license fee, royalty, or other charge for exercise of
|
466 |
+
rights granted under this License, and you may not initiate litigation
|
467 |
+
(including a cross-claim or counterclaim in a lawsuit) alleging that
|
468 |
+
any patent claim is infringed by making, using, selling, offering for
|
469 |
+
sale, or importing the Program or any portion of it.
|
470 |
+
|
471 |
+
11. Patents.
|
472 |
+
|
473 |
+
A "contributor" is a copyright holder who authorizes use under this
|
474 |
+
License of the Program or a work on which the Program is based. The
|
475 |
+
work thus licensed is called the contributor's "contributor version".
|
476 |
+
|
477 |
+
A contributor's "essential patent claims" are all patent claims
|
478 |
+
owned or controlled by the contributor, whether already acquired or
|
479 |
+
hereafter acquired, that would be infringed by some manner, permitted
|
480 |
+
by this License, of making, using, or selling its contributor version,
|
481 |
+
but do not include claims that would be infringed only as a
|
482 |
+
consequence of further modification of the contributor version. For
|
483 |
+
purposes of this definition, "control" includes the right to grant
|
484 |
+
patent sublicenses in a manner consistent with the requirements of
|
485 |
+
this License.
|
486 |
+
|
487 |
+
Each contributor grants you a non-exclusive, worldwide, royalty-free
|
488 |
+
patent license under the contributor's essential patent claims, to
|
489 |
+
make, use, sell, offer for sale, import and otherwise run, modify and
|
490 |
+
propagate the contents of its contributor version.
|
491 |
+
|
492 |
+
In the following three paragraphs, a "patent license" is any express
|
493 |
+
agreement or commitment, however denominated, not to enforce a patent
|
494 |
+
(such as an express permission to practice a patent or covenant not to
|
495 |
+
sue for patent infringement). To "grant" such a patent license to a
|
496 |
+
party means to make such an agreement or commitment not to enforce a
|
497 |
+
patent against the party.
|
498 |
+
|
499 |
+
If you convey a covered work, knowingly relying on a patent license,
|
500 |
+
and the Corresponding Source of the work is not available for anyone
|
501 |
+
to copy, free of charge and under the terms of this License, through a
|
502 |
+
publicly available network server or other readily accessible means,
|
503 |
+
then you must either (1) cause the Corresponding Source to be so
|
504 |
+
available, or (2) arrange to deprive yourself of the benefit of the
|
505 |
+
patent license for this particular work, or (3) arrange, in a manner
|
506 |
+
consistent with the requirements of this License, to extend the patent
|
507 |
+
license to downstream recipients. "Knowingly relying" means you have
|
508 |
+
actual knowledge that, but for the patent license, your conveying the
|
509 |
+
covered work in a country, or your recipient's use of the covered work
|
510 |
+
in a country, would infringe one or more identifiable patents in that
|
511 |
+
country that you have reason to believe are valid.
|
512 |
+
|
513 |
+
If, pursuant to or in connection with a single transaction or
|
514 |
+
arrangement, you convey, or propagate by procuring conveyance of, a
|
515 |
+
covered work, and grant a patent license to some of the parties
|
516 |
+
receiving the covered work authorizing them to use, propagate, modify
|
517 |
+
or convey a specific copy of the covered work, then the patent license
|
518 |
+
you grant is automatically extended to all recipients of the covered
|
519 |
+
work and works based on it.
|
520 |
+
|
521 |
+
A patent license is "discriminatory" if it does not include within
|
522 |
+
the scope of its coverage, prohibits the exercise of, or is
|
523 |
+
conditioned on the non-exercise of one or more of the rights that are
|
524 |
+
specifically granted under this License. You may not convey a covered
|
525 |
+
work if you are a party to an arrangement with a third party that is
|
526 |
+
in the business of distributing software, under which you make payment
|
527 |
+
to the third party based on the extent of your activity of conveying
|
528 |
+
the work, and under which the third party grants, to any of the
|
529 |
+
parties who would receive the covered work from you, a discriminatory
|
530 |
+
patent license (a) in connection with copies of the covered work
|
531 |
+
conveyed by you (or copies made from those copies), or (b) primarily
|
532 |
+
for and in connection with specific products or compilations that
|
533 |
+
contain the covered work, unless you entered into that arrangement,
|
534 |
+
or that patent license was granted, prior to 28 March 2007.
|
535 |
+
|
536 |
+
Nothing in this License shall be construed as excluding or limiting
|
537 |
+
any implied license or other defenses to infringement that may
|
538 |
+
otherwise be available to you under applicable patent law.
|
539 |
+
|
540 |
+
12. No Surrender of Others' Freedom.
|
541 |
+
|
542 |
+
If conditions are imposed on you (whether by court order, agreement or
|
543 |
+
otherwise) that contradict the conditions of this License, they do not
|
544 |
+
excuse you from the conditions of this License. If you cannot convey a
|
545 |
+
covered work so as to satisfy simultaneously your obligations under this
|
546 |
+
License and any other pertinent obligations, then as a consequence you may
|
547 |
+
not convey it at all. For example, if you agree to terms that obligate you
|
548 |
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to collect a royalty for further conveying from those to whom you convey
|
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the Program, the only way you could satisfy both those terms and this
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550 |
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|
551 |
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|
552 |
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|
553 |
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|
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555 |
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556 |
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557 |
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|
558 |
+
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|
559 |
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|
560 |
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|
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|
562 |
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|
563 |
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14. Revised Versions of this License.
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|
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|
567 |
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|
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581 |
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582 |
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|
583 |
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Later license versions may give you additional or different
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585 |
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586 |
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589 |
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15. Disclaimer of Warranty.
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THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
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APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
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IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
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|
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|
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|
612 |
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17. Interpretation of Sections 15 and 16.
|
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|
614 |
+
If the disclaimer of warranty and limitation of liability provided
|
615 |
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|
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|
617 |
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618 |
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|
619 |
+
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|
620 |
+
|
621 |
+
END OF TERMS AND CONDITIONS
|
622 |
+
|
623 |
+
How to Apply These Terms to Your New Programs
|
624 |
+
|
625 |
+
If you develop a new program, and you want it to be of the greatest
|
626 |
+
possible use to the public, the best way to achieve this is to make it
|
627 |
+
free software which everyone can redistribute and change under these terms.
|
628 |
+
|
629 |
+
To do so, attach the following notices to the program. It is safest
|
630 |
+
to attach them to the start of each source file to most effectively
|
631 |
+
state the exclusion of warranty; and each file should have at least
|
632 |
+
the "copyright" line and a pointer to where the full notice is found.
|
633 |
+
|
634 |
+
<one line to give the program's name and a brief idea of what it does.>
|
635 |
+
Copyright (C) <year> <name of author>
|
636 |
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|
637 |
+
This program is free software: you can redistribute it and/or modify
|
638 |
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639 |
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640 |
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641 |
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642 |
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This program is distributed in the hope that it will be useful,
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|
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645 |
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+
|
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You should have received a copy of the GNU General Public License
|
648 |
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along with this program. If not, see <https://www.gnu.org/licenses/>.
|
649 |
+
|
650 |
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Also add information on how to contact you by electronic and paper mail.
|
651 |
+
|
652 |
+
If the program does terminal interaction, make it output a short
|
653 |
+
notice like this when it starts in an interactive mode:
|
654 |
+
|
655 |
+
<program> Copyright (C) <year> <name of author>
|
656 |
+
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
|
657 |
+
This is free software, and you are welcome to redistribute it
|
658 |
+
under certain conditions; type `show c' for details.
|
659 |
+
|
660 |
+
The hypothetical commands `show w' and `show c' should show the appropriate
|
661 |
+
parts of the General Public License. Of course, your program's commands
|
662 |
+
might be different; for a GUI interface, you would use an "about box".
|
663 |
+
|
664 |
+
You should also get your employer (if you work as a programmer) or school,
|
665 |
+
if any, to sign a "copyright disclaimer" for the program, if necessary.
|
666 |
+
For more information on this, and how to apply and follow the GNU GPL, see
|
667 |
+
<https://www.gnu.org/licenses/>.
|
668 |
+
|
669 |
+
The GNU General Public License does not permit incorporating your program
|
670 |
+
into proprietary programs. If your program is a subroutine library, you
|
671 |
+
may consider it more useful to permit linking proprietary applications with
|
672 |
+
the library. If this is what you want to do, use the GNU Lesser General
|
673 |
+
Public License instead of this License. But first, please read
|
674 |
+
<https://www.gnu.org/licenses/why-not-lgpl.html>.
|
README.md
ADDED
@@ -0,0 +1,39 @@
|
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|
|
|
|
|
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|
|
|
|
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|
|
|
|
1 |
+
---
|
2 |
+
title: Omni-Zero-Couples
|
3 |
+
emoji: 🧛🏻♂️
|
4 |
+
colorFrom: purple
|
5 |
+
colorTo: red
|
6 |
+
sdk: gradio
|
7 |
+
sdk_version: 4.36.1
|
8 |
+
app_file: app.py
|
9 |
+
pinned: false
|
10 |
+
license: gpl-3.0
|
11 |
+
---
|
12 |
+
|
13 |
+
# Omni-Zero-Couples: A diffusion pipeline for zero-shot stylized couples portrait creation.
|
14 |
+
|
15 |
+
## Use Omni-Zero in HuggingFace Spaces ZeroGPU [https://huggingface.co/spaces/okaris/omni-zero-couples](https://huggingface.co/spaces/okaris/omni-zero-couples)
|
16 |
+
![Omni-Zero-Couples](https://github.com/okaris/omni-zero-couples/assets/1448702/1d4c40e0-41c5-4127-ba06-aec52a2d179d)
|
17 |
+
|
18 |
+
## Run on Replicate [https://replicate.com/okaris/omni-zero-couples](https://replicate.com/okaris/omni-zero-couples)
|
19 |
+
![Omni-Zero-Couples](https://github.com/okaris/omni-zero-couples/assets/1448702/0d53489b-89eb-4277-907f-4317cc98db74)
|
20 |
+
|
21 |
+
### Multiple Identities and Styles
|
22 |
+
![Omni-Zero-Couples](https://github.com/okaris/omni-zero-couples/assets/1448702/c5c20961-83bc-47f7-86ed-5948d5590f07)
|
23 |
+
|
24 |
+
### Single Identity and Style [https://github.com/okaris/omni-zero](https://github.com/okaris/omni-zero)
|
25 |
+
![Omni-Zero](https://github.com/okaris/omni-zero/assets/1448702/2c51fb77-a810-4c0a-9555-791a294455ca)
|
26 |
+
|
27 |
+
### How to run
|
28 |
+
```
|
29 |
+
git clone https://github.com/okaris/omni-zero-couples.git
|
30 |
+
cd omni-zero-couples
|
31 |
+
pip install -r requirements.txt
|
32 |
+
python demo.py
|
33 |
+
```
|
34 |
+
|
35 |
+
### Credits
|
36 |
+
- Special thanks to my friend Misch Strotz, Co-Founder of [letz.ai](https://letz.ai) for providing compute for the research
|
37 |
+
- This project wouldn't be possible without the great work of the [InstantX Team](https://github.com/InstantID)
|
38 |
+
- Thanks to [@fofrAI](http://twitter.com/fofrAI) for inspiring me with his [face-to-many workflow](https://github.com/fofr/cog-face-to-many)
|
39 |
+
- Thanks to Matteo ([@cubiq](https://twitter.com/cubiq])) for creating the ComfyUI nodes for IP-Adapter which inspired the quality improvements for diffusers
|
app.py
ADDED
@@ -0,0 +1,147 @@
|
|
|
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|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import gradio as gr
|
2 |
+
import spaces
|
3 |
+
import os
|
4 |
+
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
|
5 |
+
|
6 |
+
import torch
|
7 |
+
|
8 |
+
#Hack for ZeroGPU
|
9 |
+
torch.jit.script = lambda f: f
|
10 |
+
####
|
11 |
+
|
12 |
+
base_model="frankjoshua/albedobaseXL_v13"
|
13 |
+
from omni_zero import OmniZeroCouple
|
14 |
+
|
15 |
+
omni_zero = OmniZeroCouple(
|
16 |
+
base_model="frankjoshua/albedobaseXL_v13",
|
17 |
+
device="cuda",
|
18 |
+
)
|
19 |
+
|
20 |
+
@spaces.GPU()
|
21 |
+
def generate(
|
22 |
+
base_image="https://cdn-prod.styleof.com/inferences/cm1ho5cjl14nh14jec6phg2h8/i6k59e7gpsr45ufc7l8kun0g-medium.jpeg",
|
23 |
+
style_image="https://cdn-prod.styleof.com/inferences/cm1ho5cjl14nh14jec6phg2h8/i6k59e7gpsr45ufc7l8kun0g-medium.jpeg",
|
24 |
+
identity_image_1="https://cdn-prod.styleof.com/inferences/cm1hp4lea14oz14jeoghnex7g/dlgc5xwo0qzey7qaixy45i1o-medium.jpeg",
|
25 |
+
identity_image_2="https://cdn-prod.styleof.com/inferences/cm1ho69ha14np14jesnusqiep/mp3aaktzqz20ujco5i3bi5s1-medium.jpeg",
|
26 |
+
seed=42,
|
27 |
+
prompt="Cinematic still photo of a couple. emotional, harmonious, vignette, 4k epic detailed, shot on kodak, 35mm photo, sharp focus, high budget, cinemascope, moody, epic, gorgeous, film grain, grainy",
|
28 |
+
negative_prompt="anime, cartoon, graphic, (blur, blurry, bokeh), text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
|
29 |
+
guidance_scale=3.0,
|
30 |
+
number_of_images=1,
|
31 |
+
number_of_steps=10,
|
32 |
+
base_image_strength=0.3,
|
33 |
+
style_image_strength=1.0,
|
34 |
+
identity_image_strength_1=1.0,
|
35 |
+
identity_image_strength_2=1.0,
|
36 |
+
depth_image=None,
|
37 |
+
depth_image_strength=0.2,
|
38 |
+
mask_guidance_start=0.0,
|
39 |
+
mask_guidance_end=1.0,
|
40 |
+
progress=gr.Progress(track_tqdm=True)
|
41 |
+
):
|
42 |
+
images = omni_zero.generate(
|
43 |
+
seed=seed,
|
44 |
+
prompt=prompt,
|
45 |
+
negative_prompt=negative_prompt,
|
46 |
+
guidance_scale=guidance_scale,
|
47 |
+
number_of_images=number_of_images,
|
48 |
+
number_of_steps=number_of_steps,
|
49 |
+
base_image=base_image,
|
50 |
+
base_image_strength=base_image_strength,
|
51 |
+
style_image=style_image,
|
52 |
+
style_image_strength=style_image_strength,
|
53 |
+
identity_image_1=identity_image_1,
|
54 |
+
identity_image_strength_1=identity_image_strength_1,
|
55 |
+
identity_image_2=identity_image_2,
|
56 |
+
identity_image_strength_2=identity_image_strength_2,
|
57 |
+
depth_image=depth_image,
|
58 |
+
depth_image_strength=depth_image_strength,
|
59 |
+
mask_guidance_start=mask_guidance_start,
|
60 |
+
mask_guidance_end=mask_guidance_end,
|
61 |
+
)
|
62 |
+
|
63 |
+
return images
|
64 |
+
|
65 |
+
#Move the components in the example fields outside so they are available when gr.Examples is instantiated
|
66 |
+
|
67 |
+
with gr.Blocks() as demo:
|
68 |
+
gr.Markdown("<h1 style='text-align: center'>Omni Zero</h1>")
|
69 |
+
gr.Markdown("<h4 style='text-align: center'>A diffusion pipeline for zero-shot stylized portrait creation [<a href='https://github.com/okaris/omni-zero' target='_blank'>GitHub</a>], [<a href='https://styleof.com/s/remix-yourself' target='_blank'>StyleOf Remix Yourself</a>]</h4>")
|
70 |
+
with gr.Row():
|
71 |
+
with gr.Column():
|
72 |
+
with gr.Row():
|
73 |
+
prompt = gr.Textbox(label="Prompt", value="A person")
|
74 |
+
with gr.Row():
|
75 |
+
negative_prompt = gr.Textbox(label="Negative Prompt", value="blurry, out of focus")
|
76 |
+
with gr.Row():
|
77 |
+
with gr.Column(min_width=140):
|
78 |
+
with gr.Row():
|
79 |
+
composition_image = gr.Image(label="Composition")
|
80 |
+
with gr.Row():
|
81 |
+
composition_image_strength = gr.Slider(label="Strength",step=0.01, minimum=0.0, maximum=1.0, value=1.0)
|
82 |
+
#with gr.Row():
|
83 |
+
with gr.Column(min_width=140):
|
84 |
+
with gr.Row():
|
85 |
+
style_image = gr.Image(label="Style Image")
|
86 |
+
with gr.Row():
|
87 |
+
style_image_strength = gr.Slider(label="Strength",step=0.01, minimum=0.0, maximum=1.0, value=1.0)
|
88 |
+
with gr.Column(min_width=140):
|
89 |
+
with gr.Row():
|
90 |
+
identity_image = gr.Image(label="Identity Image")
|
91 |
+
with gr.Row():
|
92 |
+
identity_image_strength = gr.Slider(label="Strenght",step=0.01, minimum=0.0, maximum=1.0, value=1.0)
|
93 |
+
with gr.Accordion("Advanced options", open=False):
|
94 |
+
with gr.Row():
|
95 |
+
with gr.Column(min_width=140):
|
96 |
+
with gr.Row():
|
97 |
+
base_image = gr.Image(label="Base Image")
|
98 |
+
with gr.Row():
|
99 |
+
base_image_strength = gr.Slider(label="Strength",step=0.01, minimum=0.0, maximum=1.0, value=0.15, min_width=120)
|
100 |
+
# with gr.Column(min_width=140):
|
101 |
+
# with gr.Row():
|
102 |
+
# depth_image = gr.Image(label="depth_image", value=None)
|
103 |
+
# with gr.Row():
|
104 |
+
# depth_image_strength = gr.Slider(label="depth_image_strength",step=0.01, minimum=0.0, maximum=1.0, value=0.5)
|
105 |
+
|
106 |
+
with gr.Row():
|
107 |
+
seed = gr.Slider(label="Seed",step=1, minimum=0, maximum=10000000, value=42)
|
108 |
+
number_of_images = gr.Slider(label="Number of Outputs",step=1, minimum=1, maximum=4, value=1)
|
109 |
+
with gr.Row():
|
110 |
+
guidance_scale = gr.Slider(label="Guidance Scale",step=0.1, minimum=0.0, maximum=14.0, value=3.0)
|
111 |
+
number_of_steps = gr.Slider(label="Number of Steps",step=1, minimum=1, maximum=50, value=10)
|
112 |
+
|
113 |
+
with gr.Column():
|
114 |
+
with gr.Row():
|
115 |
+
out = gr.Gallery(label="Output(s)")
|
116 |
+
with gr.Row():
|
117 |
+
# clear = gr.Button("Clear")
|
118 |
+
submit = gr.Button("Generate")
|
119 |
+
|
120 |
+
submit.click(generate, inputs=[
|
121 |
+
prompt,
|
122 |
+
composition_image,
|
123 |
+
style_image,
|
124 |
+
identity_image,
|
125 |
+
base_image,
|
126 |
+
seed,
|
127 |
+
negative_prompt,
|
128 |
+
guidance_scale,
|
129 |
+
number_of_images,
|
130 |
+
number_of_steps,
|
131 |
+
base_image_strength,
|
132 |
+
composition_image_strength,
|
133 |
+
style_image_strength,
|
134 |
+
identity_image_strength,
|
135 |
+
],
|
136 |
+
outputs=[out]
|
137 |
+
)
|
138 |
+
# clear.click(lambda: None, None, chatbot, queue=False)
|
139 |
+
gr.Examples(
|
140 |
+
examples=[["A person", "https://github.com/okaris/omni-zero/assets/1448702/2ca63443-c7f3-4ba6-95c1-2a341414865f", "https://github.com/okaris/omni-zero/assets/1448702/64dc150b-f683-41b1-be23-b6a52c771584", "https://github.com/okaris/omni-zero/assets/1448702/ba193a3a-f90e-4461-848a-560454531c58"]],
|
141 |
+
inputs=[prompt, composition_image, style_image, identity_image],
|
142 |
+
outputs=[out],
|
143 |
+
fn=generate,
|
144 |
+
cache_examples="lazy",
|
145 |
+
)
|
146 |
+
if __name__ == "__main__":
|
147 |
+
demo.launch()
|
cog.yaml
ADDED
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Configuration for Cog ⚙️
|
2 |
+
# Reference: https://github.com/replicate/cog/blob/main/docs/yaml.md
|
3 |
+
|
4 |
+
build:
|
5 |
+
# set to true if your model requires a GPU
|
6 |
+
gpu: true
|
7 |
+
|
8 |
+
# a list of ubuntu apt packages to install
|
9 |
+
system_packages:
|
10 |
+
- "libgl1-mesa-glx"
|
11 |
+
- "libglib2.0-0"
|
12 |
+
|
13 |
+
# python version in the form '3.8' or '3.8.12'
|
14 |
+
python_version: "3.11"
|
15 |
+
python_requirements: "requirements.txt"
|
16 |
+
|
17 |
+
# a list of packages in the format <package-name>==<version>
|
18 |
+
# python_packages:
|
19 |
+
# - "numpy==1.19.4"
|
20 |
+
# - "torch==1.8.0"
|
21 |
+
# - "torchvision==0.9.0"
|
22 |
+
|
23 |
+
# commands run after the environment is setup
|
24 |
+
# run:
|
25 |
+
# - "echo env is ready!"
|
26 |
+
# - "echo another command if needed"
|
27 |
+
|
28 |
+
# predict.py defines how predictions are run on your model
|
29 |
+
predict: "predict.py:Predictor"
|
demo.py
ADDED
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from omni_zero import OmniZeroCouple
|
2 |
+
|
3 |
+
def demo():
|
4 |
+
omni_zero = OmniZeroCouple(
|
5 |
+
base_model="frankjoshua/albedobaseXL_v13",
|
6 |
+
device="cuda",
|
7 |
+
)
|
8 |
+
|
9 |
+
base_image="https://cdn-prod.styleof.com/inferences/cm1ho5cjl14nh14jec6phg2h8/i6k59e7gpsr45ufc7l8kun0g-medium.jpeg"
|
10 |
+
style_image="https://cdn-prod.styleof.com/inferences/cm1ho5cjl14nh14jec6phg2h8/i6k59e7gpsr45ufc7l8kun0g-medium.jpeg"
|
11 |
+
identity_image_1="https://ichef.bbci.co.uk/images/ic/1040x1040/p0f5vv8q.jpg"#"https://cdn-prod.styleof.com/inferences/cm1hp4lea14oz14jeoghnex7g/dlgc5xwo0qzey7qaixy45i1o-medium.jpeg"
|
12 |
+
identity_image_2="https://www.judentum-projekt.de/images/meitner22-2_640.jpg"#"https://cdn-prod.styleof.com/inferences/cm1ho69ha14np14jesnusqiep/mp3aaktzqz20ujco5i3bi5s1-medium.jpeg"
|
13 |
+
|
14 |
+
images = omni_zero.generate(
|
15 |
+
seed=42,
|
16 |
+
prompt="Cinematic still photo of a couple. emotional, harmonious, vignette, 4k epic detailed, shot on kodak, 35mm photo, sharp focus, high budget, cinemascope, moody, epic, gorgeous, film grain, grainy",
|
17 |
+
negative_prompt="anime, cartoon, graphic, (blur, blurry, bokeh), text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
|
18 |
+
guidance_scale=3.0,
|
19 |
+
number_of_images=1,
|
20 |
+
number_of_steps=10,
|
21 |
+
base_image=base_image,
|
22 |
+
base_image_strength=0.3,
|
23 |
+
style_image=style_image,
|
24 |
+
style_image_strength=1.0,
|
25 |
+
identity_image_1=identity_image_1,
|
26 |
+
identity_image_strength_1=1.0,
|
27 |
+
identity_image_2=identity_image_2,
|
28 |
+
identity_image_strength_2=1.0,
|
29 |
+
depth_image=None,
|
30 |
+
depth_image_strength=0.2,
|
31 |
+
mask_guidance_start=0.0,
|
32 |
+
mask_guidance_end=1.0,
|
33 |
+
)
|
34 |
+
|
35 |
+
for i, image in enumerate(images):
|
36 |
+
image.save(f"oz_output_{i}.jpg")
|
37 |
+
|
38 |
+
if __name__ == "__main__":
|
39 |
+
demo()
|
omni_zero.py
ADDED
@@ -0,0 +1,229 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os
|
2 |
+
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
|
3 |
+
|
4 |
+
import sys
|
5 |
+
sys.path.insert(0, './diffusers/src')
|
6 |
+
|
7 |
+
import torch
|
8 |
+
import torch.nn as nn
|
9 |
+
|
10 |
+
from huggingface_hub import snapshot_download
|
11 |
+
from diffusers import DPMSolverMultistepScheduler
|
12 |
+
from diffusers.models import ControlNetModel
|
13 |
+
from diffusers.image_processor import IPAdapterMaskProcessor
|
14 |
+
|
15 |
+
from transformers import CLIPVisionModelWithProjection
|
16 |
+
|
17 |
+
from pipeline import OmniZeroPipeline
|
18 |
+
from insightface.app import FaceAnalysis
|
19 |
+
from controlnet_aux import ZoeDetector
|
20 |
+
from utils import draw_kps, load_and_resize_image, align_images
|
21 |
+
|
22 |
+
from pydantic import BaseModel, Field
|
23 |
+
|
24 |
+
import cv2
|
25 |
+
import numpy as np
|
26 |
+
from torchvision.transforms import functional as TVF
|
27 |
+
|
28 |
+
import PIL
|
29 |
+
|
30 |
+
class OmniZeroCouple():
|
31 |
+
def __init__(self,
|
32 |
+
base_model="stabilityai/stable-diffusion-xl-base-1.0",
|
33 |
+
device="cuda",
|
34 |
+
):
|
35 |
+
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
|
36 |
+
self.patch_onnx_runtime()
|
37 |
+
|
38 |
+
snapshot_download("okaris/antelopev2", local_dir="./models/antelopev2")
|
39 |
+
self.face_analysis = FaceAnalysis(name='antelopev2', root='./', providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
|
40 |
+
self.face_analysis.prepare(ctx_id=0, det_size=(640, 640))
|
41 |
+
|
42 |
+
self.dtype = dtype = torch.float16
|
43 |
+
|
44 |
+
ip_adapter_plus_image_encoder = CLIPVisionModelWithProjection.from_pretrained(
|
45 |
+
"h94/IP-Adapter",
|
46 |
+
subfolder="models/image_encoder",
|
47 |
+
torch_dtype=dtype,
|
48 |
+
).to(device)
|
49 |
+
|
50 |
+
zoedepthnet_path = "okaris/zoe-depth-controlnet-xl"
|
51 |
+
zoedepthnet = ControlNetModel.from_pretrained(zoedepthnet_path,torch_dtype=dtype).to(device)
|
52 |
+
|
53 |
+
identitiynet_path = "okaris/face-controlnet-xl"
|
54 |
+
identitynet = ControlNetModel.from_pretrained(identitiynet_path, torch_dtype=dtype).to(device)
|
55 |
+
|
56 |
+
self.zoe_depth_detector = ZoeDetector.from_pretrained("lllyasviel/Annotators").to(device)
|
57 |
+
self.ip_adapter_mask_processor = IPAdapterMaskProcessor()
|
58 |
+
|
59 |
+
self.pipeline = OmniZeroPipeline.from_pretrained(
|
60 |
+
base_model,
|
61 |
+
controlnet=[identitynet, identitynet, zoedepthnet],
|
62 |
+
torch_dtype=dtype,
|
63 |
+
image_encoder=ip_adapter_plus_image_encoder,
|
64 |
+
).to(device)
|
65 |
+
|
66 |
+
config = self.pipeline.scheduler.config
|
67 |
+
config["timestep_spacing"] = "trailing"
|
68 |
+
self.pipeline.scheduler = DPMSolverMultistepScheduler.from_config(config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++", final_sigmas_type="zero")
|
69 |
+
|
70 |
+
self.pipeline.load_ip_adapter(["okaris/ip-adapter-instantid", "okaris/ip-adapter-instantid", "h94/IP-Adapter"], subfolder=[None, None, "sdxl_models"], weight_name=["ip-adapter-instantid.bin", "ip-adapter-instantid.bin", "ip-adapter-plus_sdxl_vit-h.safetensors"])
|
71 |
+
|
72 |
+
def generate(self,
|
73 |
+
seed=42,
|
74 |
+
prompt="A person",
|
75 |
+
negative_prompt="blurry, out of focus",
|
76 |
+
guidance_scale=3.0,
|
77 |
+
number_of_images=1,
|
78 |
+
number_of_steps=10,
|
79 |
+
base_image=None,
|
80 |
+
base_image_strength=0.15,
|
81 |
+
style_image=None,
|
82 |
+
style_image_strength=1.0,
|
83 |
+
identity_image_1=None,
|
84 |
+
identity_image_strength_1=1.0,
|
85 |
+
identity_image_2=None,
|
86 |
+
identity_image_strength_2=1.0,
|
87 |
+
depth_image=None,
|
88 |
+
depth_image_strength=0.5,
|
89 |
+
mask_guidance_start=0.0,
|
90 |
+
mask_guidance_end=1.0,
|
91 |
+
):
|
92 |
+
|
93 |
+
resolution = 1024
|
94 |
+
|
95 |
+
if base_image is not None:
|
96 |
+
base_image = load_and_resize_image(base_image, resolution, resolution)
|
97 |
+
|
98 |
+
if depth_image is None:
|
99 |
+
depth_image = self.zoe_depth_detector(base_image, detect_resolution=resolution, image_resolution=resolution)
|
100 |
+
else:
|
101 |
+
depth_image = load_and_resize_image(depth_image, resolution, resolution)
|
102 |
+
|
103 |
+
base_image, depth_image = align_images(base_image, depth_image)
|
104 |
+
|
105 |
+
if style_image is not None:
|
106 |
+
style_image = load_and_resize_image(style_image, resolution, resolution)
|
107 |
+
else:
|
108 |
+
raise ValueError("You must provide a style image")
|
109 |
+
|
110 |
+
if identity_image_1 is not None:
|
111 |
+
identity_image_1 = load_and_resize_image(identity_image_1, resolution, resolution)
|
112 |
+
else:
|
113 |
+
raise ValueError("You must provide an identity image")
|
114 |
+
|
115 |
+
if identity_image_2 is not None:
|
116 |
+
identity_image_2 = load_and_resize_image(identity_image_2, resolution, resolution)
|
117 |
+
else:
|
118 |
+
raise ValueError("You must provide an identity image 2")
|
119 |
+
|
120 |
+
height, width = base_image.size
|
121 |
+
|
122 |
+
face_info_1 = self.face_analysis.get(cv2.cvtColor(np.array(identity_image_1), cv2.COLOR_RGB2BGR))
|
123 |
+
for i, face in enumerate(face_info_1):
|
124 |
+
print(f"Face 1 -{i}: Age: {face['age']}, Gender: {face['gender']}")
|
125 |
+
face_info_1 = sorted(face_info_1, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])[-1] # only use the maximum face
|
126 |
+
face_emb_1 = torch.tensor(face_info_1['embedding']).to("cuda", dtype=self.dtype)
|
127 |
+
|
128 |
+
face_info_2 = self.face_analysis.get(cv2.cvtColor(np.array(identity_image_2), cv2.COLOR_RGB2BGR))
|
129 |
+
for i, face in enumerate(face_info_2):
|
130 |
+
print(f"Face 2 -{i}: Age: {face['age']}, Gender: {face['gender']}")
|
131 |
+
face_info_2 = sorted(face_info_2, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])[-1] # only use the maximum face
|
132 |
+
face_emb_2 = torch.tensor(face_info_2['embedding']).to("cuda", dtype=self.dtype)
|
133 |
+
|
134 |
+
zero = np.zeros((width, height, 3), dtype=np.uint8)
|
135 |
+
# face_kps_identity_image_1 = self.draw_kps(zero, face_info_1['kps'])
|
136 |
+
# face_kps_identity_image_2 = self.draw_kps(zero, face_info_2['kps'])
|
137 |
+
|
138 |
+
face_info_img2img = self.face_analysis.get(cv2.cvtColor(np.array(base_image), cv2.COLOR_RGB2BGR))
|
139 |
+
faces_info_img2img = sorted(face_info_img2img, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])
|
140 |
+
face_info_a = faces_info_img2img[-1]
|
141 |
+
face_info_b = faces_info_img2img[-2]
|
142 |
+
# face_emb_a = torch.tensor(face_info_a['embedding']).to("cuda", dtype=self.dtype)
|
143 |
+
# face_emb_b = torch.tensor(face_info_b['embedding']).to("cuda", dtype=self.dtype)
|
144 |
+
face_kps_identity_image_a = draw_kps(zero, face_info_a['kps'])
|
145 |
+
face_kps_identity_image_b = draw_kps(zero, face_info_b['kps'])
|
146 |
+
|
147 |
+
general_mask = PIL.Image.fromarray(np.ones((width, height, 3), dtype=np.uint8))
|
148 |
+
|
149 |
+
control_mask_1 = zero.copy()
|
150 |
+
x1, y1, x2, y2 = face_info_a["bbox"]
|
151 |
+
x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
|
152 |
+
control_mask_1[y1:y2, x1:x2] = 255
|
153 |
+
control_mask_1 = PIL.Image.fromarray(control_mask_1.astype(np.uint8))
|
154 |
+
|
155 |
+
control_mask_2 = zero.copy()
|
156 |
+
x1, y1, x2, y2 = face_info_b["bbox"]
|
157 |
+
x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
|
158 |
+
control_mask_2[y1:y2, x1:x2] = 255
|
159 |
+
control_mask_2 = PIL.Image.fromarray(control_mask_2.astype(np.uint8))
|
160 |
+
|
161 |
+
controlnet_masks = [control_mask_1, control_mask_2, general_mask]
|
162 |
+
ip_adapter_images = [face_emb_1, face_emb_2, style_image, ]
|
163 |
+
|
164 |
+
masks = self.ip_adapter_mask_processor.preprocess([control_mask_1, control_mask_2, general_mask], height=height, width=width)
|
165 |
+
ip_adapter_masks = [mask.unsqueeze(0) for mask in masks]
|
166 |
+
|
167 |
+
inpaint_mask = torch.logical_or(torch.tensor(np.array(control_mask_1)), torch.tensor(np.array(control_mask_2))).float()
|
168 |
+
inpaint_mask = PIL.Image.fromarray((inpaint_mask.numpy() * 255).astype(np.uint8)).convert("RGB")
|
169 |
+
|
170 |
+
new_ip_adapter_masks = []
|
171 |
+
for ip_img, mask in zip(ip_adapter_images, controlnet_masks):
|
172 |
+
if isinstance(ip_img, list):
|
173 |
+
num_images = len(ip_img)
|
174 |
+
mask = mask.repeat(1, num_images, 1, 1)
|
175 |
+
|
176 |
+
new_ip_adapter_masks.append(mask)
|
177 |
+
|
178 |
+
generator = torch.Generator(device="cpu").manual_seed(seed)
|
179 |
+
|
180 |
+
self.pipeline.set_ip_adapter_scale([identity_image_strength_1, identity_image_strength_2,
|
181 |
+
{
|
182 |
+
"down": { "block_2": [0.0, 0.0] }, #Composition
|
183 |
+
"up": { "block_0": [0.0, style_image_strength, 0.0] } #Style
|
184 |
+
}
|
185 |
+
])
|
186 |
+
|
187 |
+
images = self.pipeline(
|
188 |
+
prompt=prompt,
|
189 |
+
negative_prompt=negative_prompt,
|
190 |
+
guidance_scale=guidance_scale,
|
191 |
+
num_inference_steps=number_of_steps,
|
192 |
+
num_images_per_prompt=number_of_images,
|
193 |
+
ip_adapter_image=ip_adapter_images,
|
194 |
+
cross_attention_kwargs={"ip_adapter_masks": ip_adapter_masks},
|
195 |
+
image=base_image,
|
196 |
+
mask_image=inpaint_mask,
|
197 |
+
i2i_mask_guidance_start=mask_guidance_start,
|
198 |
+
i2i_mask_guidance_end=mask_guidance_end,
|
199 |
+
control_image=[face_kps_identity_image_a, face_kps_identity_image_b, depth_image],
|
200 |
+
control_mask=controlnet_masks,
|
201 |
+
identity_control_indices=[(0,0), (1,1)],
|
202 |
+
controlnet_conditioning_scale=[identity_image_strength_1, identity_image_strength_2, depth_image_strength],
|
203 |
+
strength=1-base_image_strength,
|
204 |
+
generator=generator,
|
205 |
+
seed=seed,
|
206 |
+
).images
|
207 |
+
|
208 |
+
return images
|
209 |
+
|
210 |
+
def patch_onnx_runtime(
|
211 |
+
self,
|
212 |
+
inter_op_num_threads: int = 16,
|
213 |
+
intra_op_num_threads: int = 16,
|
214 |
+
omp_num_threads: int = 16,
|
215 |
+
):
|
216 |
+
import os
|
217 |
+
import onnxruntime as ort
|
218 |
+
|
219 |
+
os.environ["OMP_NUM_THREADS"] = str(omp_num_threads)
|
220 |
+
|
221 |
+
_default_session_options = ort.capi._pybind_state.get_default_session_options()
|
222 |
+
|
223 |
+
def get_default_session_options_new():
|
224 |
+
_default_session_options.inter_op_num_threads = inter_op_num_threads
|
225 |
+
_default_session_options.intra_op_num_threads = intra_op_num_threads
|
226 |
+
return _default_session_options
|
227 |
+
|
228 |
+
ort.capi._pybind_state.get_default_session_options = get_default_session_options_new
|
229 |
+
|
pipeline.py
ADDED
The diff for this file is too large to render.
See raw diff
|
|
predict.py
ADDED
@@ -0,0 +1,70 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Prediction interface for Cog ⚙️
|
2 |
+
# https://github.com/replicate/cog/blob/main/docs/python.md
|
3 |
+
|
4 |
+
from cog import BasePredictor, Input, Path
|
5 |
+
from typing import List
|
6 |
+
from omni_zero import OmniZeroCouple
|
7 |
+
|
8 |
+
class Predictor(BasePredictor):
|
9 |
+
def setup(self):
|
10 |
+
"""Load the model into memory to make running multiple predictions efficient"""
|
11 |
+
self.omni_zero = OmniZeroCouple(
|
12 |
+
base_model="frankjoshua/albedobaseXL_v13",
|
13 |
+
)
|
14 |
+
def predict(
|
15 |
+
self,
|
16 |
+
seed: int = Input(description="Random seed for the model", default=42),
|
17 |
+
prompt: str = Input(description="Prompt for the model", default="Cinematic still photo of a couple. emotional, harmonious, vignette, 4k epic detailed, shot on kodak, 35mm photo, sharp focus, high budget, cinemascope, moody, epic, gorgeous, film grain, grainy"),
|
18 |
+
negative_prompt: str = Input(description="Negative prompt for the model", default="anime, cartoon, graphic, (blur, blurry, bokeh), text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured"),
|
19 |
+
guidance_scale: float = Input(description="Guidance scale for the model", default=3.0, ge=0.0, le=14.0),
|
20 |
+
number_of_images: int = Input(description="Number of images to generate", default=1, ge=1, le=4),
|
21 |
+
number_of_steps: int = Input(description="Number of steps for the model", default=10, ge=1, le=50),
|
22 |
+
base_image: Path = Input(description="Base image for the model", default=None),
|
23 |
+
base_image_strength: float = Input(description="Base image strength for the model", default=0.3, ge=0.0, le=1.0),
|
24 |
+
style_image: Path = Input(description="Style image for the model", default=None),
|
25 |
+
style_image_strength: float = Input(description="Style image strength for the model", default=1.0, ge=0.0, le=1.0),
|
26 |
+
identity_image_1: Path = Input(description="First identity image for the model", default=None),
|
27 |
+
identity_image_strength_1: float = Input(description="First identity image strength for the model", default=1.0, ge=0.0, le=1.0),
|
28 |
+
identity_image_2: Path = Input(description="Second identity image for the model", default=None),
|
29 |
+
identity_image_strength_2: float = Input(description="Second identity image strength for the model", default=1.0, ge=0.0, le=1.0),
|
30 |
+
depth_image: Path = Input(description="Depth image for the model", default=None),
|
31 |
+
depth_image_strength: float = Input(description="Depth image strength for the model", default=0.2, ge=0.0, le=1.0),
|
32 |
+
mask_guidance_start: float = Input(description="Mask guidance start value", default=0.0, ge=0.0, le=1.0),
|
33 |
+
mask_guidance_end: float = Input(description="Mask guidance end value", default=1.0, ge=0.0, le=1.0),
|
34 |
+
) -> List[Path]:
|
35 |
+
"""Run a single prediction on the model"""
|
36 |
+
|
37 |
+
# base_image = Image.open(base_image) if base_image else None
|
38 |
+
# style_image = Image.open(style_image) if style_image else None
|
39 |
+
# identity_image_1 = Image.open(identity_image_1) if identity_image_1 else None
|
40 |
+
# identity_image_2 = Image.open(identity_image_2) if identity_image_2 else None
|
41 |
+
# depth_image = Image.open(depth_image) if depth_image else None
|
42 |
+
|
43 |
+
images = self.omni_zero.generate(
|
44 |
+
seed=seed,
|
45 |
+
prompt=prompt,
|
46 |
+
negative_prompt=negative_prompt,
|
47 |
+
guidance_scale=guidance_scale,
|
48 |
+
number_of_images=number_of_images,
|
49 |
+
number_of_steps=number_of_steps,
|
50 |
+
base_image=base_image,
|
51 |
+
base_image_strength=base_image_strength,
|
52 |
+
style_image=style_image,
|
53 |
+
style_image_strength=style_image_strength,
|
54 |
+
identity_image_1=identity_image_1,
|
55 |
+
identity_image_strength_1=identity_image_strength_1,
|
56 |
+
identity_image_2=identity_image_2,
|
57 |
+
identity_image_strength_2=identity_image_strength_2,
|
58 |
+
depth_image=depth_image,
|
59 |
+
depth_image_strength=depth_image_strength,
|
60 |
+
mask_guidance_start=mask_guidance_start,
|
61 |
+
mask_guidance_end=mask_guidance_end,
|
62 |
+
)
|
63 |
+
|
64 |
+
outputs = []
|
65 |
+
for i, image in enumerate(images):
|
66 |
+
output_path = f"oz_output_{i}.jpg"
|
67 |
+
image.save(output_path)
|
68 |
+
outputs.append(Path(output_path))
|
69 |
+
|
70 |
+
return outputs
|
requirements.txt
ADDED
@@ -0,0 +1,22 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
--extra-index-url https://download.pytorch.org/whl/cu124
|
2 |
+
accelerate
|
3 |
+
diffusers==0.30.3
|
4 |
+
controlnet_aux==0.0.9
|
5 |
+
huggingface_hub==0.25.1
|
6 |
+
# insightface==0.7.3
|
7 |
+
git+https://github.com/badayvedat/insightface.git@1ffa3405eedcfe4193c3113affcbfc294d0e684f#subdirectory=python-package
|
8 |
+
numpy==1.26.2
|
9 |
+
opencv_contrib_python==4.9.0.80
|
10 |
+
opencv_python==4.9.0.80
|
11 |
+
opencv_python_headless==4.7.0.72
|
12 |
+
Pillow==10.1.0
|
13 |
+
pydantic<2.0.0
|
14 |
+
torch==2.4.0
|
15 |
+
torchvision==0.19.0
|
16 |
+
torchaudio==2.4.0
|
17 |
+
torchsde==0.2.6
|
18 |
+
transformers==4.44.2
|
19 |
+
onnxruntime-gpu
|
20 |
+
hf_transfer
|
21 |
+
gradio
|
22 |
+
spaces
|
utils.py
ADDED
@@ -0,0 +1,168 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import math
|
2 |
+
import PIL
|
3 |
+
from PIL import Image
|
4 |
+
import cv2
|
5 |
+
import numpy as np
|
6 |
+
|
7 |
+
from diffusers.utils import load_image
|
8 |
+
|
9 |
+
def draw_kps(image_pil, kps, color_list=[(255, 0, 0), (0, 255, 0), (0, 0, 255), (255, 255, 0), (255, 0, 255)]):
|
10 |
+
"""
|
11 |
+
Draw keypoints on an image.
|
12 |
+
|
13 |
+
Args:
|
14 |
+
image_pil (PIL.Image): Image on which to draw the keypoints.
|
15 |
+
kps (list): List of keypoints to draw.
|
16 |
+
color_list (list): List of colors to use for drawing the keypoints.
|
17 |
+
|
18 |
+
Returns:
|
19 |
+
PIL.Image: Image with keypoints drawn on it.
|
20 |
+
"""
|
21 |
+
|
22 |
+
stickwidth = 4
|
23 |
+
limbSeq = np.array([[0, 2], [1, 2], [3, 2], [4, 2]])
|
24 |
+
kps = np.array(kps)
|
25 |
+
|
26 |
+
# w, h = image_pil.size
|
27 |
+
# out_img = np.zeros([h, w, 3])
|
28 |
+
if type(image_pil) == PIL.Image.Image:
|
29 |
+
out_img = np.array(image_pil)
|
30 |
+
else:
|
31 |
+
out_img = image_pil
|
32 |
+
|
33 |
+
for i in range(len(limbSeq)):
|
34 |
+
index = limbSeq[i]
|
35 |
+
color = color_list[index[0]]
|
36 |
+
|
37 |
+
x = kps[index][:, 0]
|
38 |
+
y = kps[index][:, 1]
|
39 |
+
length = ((x[0] - x[1]) ** 2 + (y[0] - y[1]) ** 2) ** 0.5
|
40 |
+
angle = math.degrees(math.atan2(y[0] - y[1], x[0] - x[1]))
|
41 |
+
polygon = cv2.ellipse2Poly(
|
42 |
+
(int(np.mean(x)), int(np.mean(y))), (int(length / 2), stickwidth), int(angle), 0, 360, 1
|
43 |
+
)
|
44 |
+
out_img = cv2.fillConvexPoly(out_img.copy(), polygon, color)
|
45 |
+
out_img = (out_img * 0.6).astype(np.uint8)
|
46 |
+
|
47 |
+
for idx_kp, kp in enumerate(kps):
|
48 |
+
color = color_list[idx_kp]
|
49 |
+
x, y = kp
|
50 |
+
out_img = cv2.circle(out_img.copy(), (int(x), int(y)), 10, color, -1)
|
51 |
+
|
52 |
+
out_img_pil = PIL.Image.fromarray(out_img.astype(np.uint8))
|
53 |
+
return out_img_pil
|
54 |
+
|
55 |
+
|
56 |
+
def load_and_resize_image(image_path, max_width, max_height, maintain_aspect_ratio=True):
|
57 |
+
"""
|
58 |
+
Load and resize an image to the specified dimensions.
|
59 |
+
|
60 |
+
Args:
|
61 |
+
image_path (str): Path to the image file.
|
62 |
+
max_width (int): Maximum width of the resized image.
|
63 |
+
max_height (int): Maximum height of the resized image.
|
64 |
+
maintain_aspect_ratio (bool): Whether to maintain the aspect ratio of the image.
|
65 |
+
|
66 |
+
Returns:
|
67 |
+
PIL.Image: Resized image.
|
68 |
+
"""
|
69 |
+
|
70 |
+
# Open the image
|
71 |
+
if isinstance(image_path, np.ndarray):
|
72 |
+
image_path = Image.fromarray(image_path)
|
73 |
+
|
74 |
+
image = load_image(image_path)
|
75 |
+
|
76 |
+
# Get the current width and height of the image
|
77 |
+
current_width, current_height = image.size
|
78 |
+
|
79 |
+
if maintain_aspect_ratio:
|
80 |
+
# Calculate the aspect ratio of the image
|
81 |
+
aspect_ratio = current_width / current_height
|
82 |
+
|
83 |
+
# Calculate the new dimensions based on the max width and height
|
84 |
+
if current_width / max_width > current_height / max_height:
|
85 |
+
new_width = max_width
|
86 |
+
new_height = int(new_width / aspect_ratio)
|
87 |
+
else:
|
88 |
+
new_height = max_height
|
89 |
+
new_width = int(new_height * aspect_ratio)
|
90 |
+
else:
|
91 |
+
# Use the max width and height as the new dimensions
|
92 |
+
new_width = max_width
|
93 |
+
new_height = max_height
|
94 |
+
|
95 |
+
# Ensure the new dimensions are divisible by 8
|
96 |
+
new_width = (new_width // 8) * 8
|
97 |
+
new_height = (new_height // 8) * 8
|
98 |
+
|
99 |
+
# Resize the image
|
100 |
+
resized_image = image.resize((new_width, new_height))
|
101 |
+
|
102 |
+
return resized_image
|
103 |
+
|
104 |
+
|
105 |
+
def align_images(image1, image2):
|
106 |
+
"""
|
107 |
+
Resize two images to the same dimensions by cropping the larger image(s) to match the smaller one.
|
108 |
+
|
109 |
+
Args:
|
110 |
+
image1 (PIL.Image): First image to be aligned.
|
111 |
+
image2 (PIL.Image): Second image to be aligned.
|
112 |
+
|
113 |
+
Returns:
|
114 |
+
tuple: A tuple containing two images with the same dimensions.
|
115 |
+
"""
|
116 |
+
# Determine the new size by taking the smaller width and height from both images
|
117 |
+
new_width = min(image1.size[0], image2.size[0])
|
118 |
+
new_height = min(image1.size[1], image2.size[1])
|
119 |
+
|
120 |
+
# Crop both images if necessary
|
121 |
+
if image1.size != (new_width, new_height):
|
122 |
+
image1 = image1.crop((0, 0, new_width, new_height))
|
123 |
+
if image2.size != (new_width, new_height):
|
124 |
+
image2 = image2.crop((0, 0, new_width, new_height))
|
125 |
+
|
126 |
+
return image1, image2
|
127 |
+
|
128 |
+
def align_images_2(image1, image2):
|
129 |
+
"""
|
130 |
+
Resize and crop the second image to match the dimensions of the first image by
|
131 |
+
scaling to aspect fill and then center cropping the extra parts.
|
132 |
+
|
133 |
+
Args:
|
134 |
+
image1 (PIL.Image): First image which will act as the reference for alignment.
|
135 |
+
image2 (PIL.Image): Second image to be aligned to the first image's dimensions.
|
136 |
+
|
137 |
+
Returns:
|
138 |
+
tuple: A tuple containing the first image and the aligned second image.
|
139 |
+
"""
|
140 |
+
# Get dimensions of the first image
|
141 |
+
target_width, target_height = image1.size
|
142 |
+
|
143 |
+
# Calculate the aspect ratio of the second image
|
144 |
+
aspect_ratio = image2.width / image2.height
|
145 |
+
|
146 |
+
# Calculate dimensions to aspect fill
|
147 |
+
if target_width / target_height > aspect_ratio:
|
148 |
+
# The first image is wider relative to its height than the second image
|
149 |
+
fill_height = target_height
|
150 |
+
fill_width = int(fill_height * aspect_ratio)
|
151 |
+
else:
|
152 |
+
# The first image is taller relative to its width than the second image
|
153 |
+
fill_width = target_width
|
154 |
+
fill_height = int(fill_width / aspect_ratio)
|
155 |
+
|
156 |
+
# Resize the second image to fill dimensions
|
157 |
+
filled_image = image2.resize((fill_width, fill_height), Image.Resampling.LANCZOS)
|
158 |
+
|
159 |
+
# Calculate top-left corner of crop box to center crop
|
160 |
+
left = (fill_width - target_width) / 2
|
161 |
+
top = (fill_height - target_height) / 2
|
162 |
+
right = left + target_width
|
163 |
+
bottom = top + target_height
|
164 |
+
|
165 |
+
# Crop the filled image to match the size of the first image
|
166 |
+
cropped_image = filled_image.crop((int(left), int(top), int(right), int(bottom)))
|
167 |
+
|
168 |
+
return image1, cropped_image
|