Spaces:
Running
on
T4
Running
on
T4
File size: 3,717 Bytes
fd1dd45 e158b55 c2aa8fe e158b55 bb4cd3c fd1dd45 4ae11c9 fd1dd45 0e5ab33 fd1dd45 19e2b6d cfa0c30 2da7508 19e2b6d c9a473f fd1dd45 2da7508 fd1dd45 c2aa8fe fd1dd45 c9a473f fd1dd45 c2aa8fe e158b55 fd1dd45 e158b55 fd1dd45 e158b55 fd1dd45 be4dbd7 c9a473f be4dbd7 e158b55 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 |
from fastapi import FastAPI, UploadFile
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
import subprocess
import os
import json
import uuid
import logging
import torch
from diffusers import (
StableDiffusionPipeline,
DPMSolverMultistepScheduler,
EulerDiscreteScheduler,
)
app = FastAPI()
@app.get("/generate")
def generate_image(prompt, model):
torch.cuda.empty_cache()
modelArray = model.split(",")
modelName = modelArray[0]
modelVersion = modelArray[1]
pipeline = StableDiffusionPipeline.from_pretrained(
str(modelName), torch_dtype=torch.float16
)
pipeline.scheduler = EulerDiscreteScheduler.from_config(pipeline.scheduler.config)
pipeline = pipeline.to("cuda")
image = pipeline(prompt, num_inference_steps=50, height=512, width=512).images[0]
filename = str(uuid.uuid4()) + ".jpg"
image.save(filename)
assertion = {
"assertions": [
{
"label": "com.truepic.custom.ai",
"data": {
"model_name": modelName,
"model_version": modelVersion,
"prompt": prompt,
},
}
]
}
json_object = json.dumps(assertion)
subprocess.check_output(
[
"./truepic",
"sign",
filename,
"--assertions-inline",
json_object,
"--output",
(os.getcwd() + "/static/" + filename),
]
)
return {"response": filename}
@app.post("/verify")
def verify_image(fileUpload: UploadFile):
logging.warning("in verify")
logging.warning(fileUpload.filename)
# check if the file has been uploaded
if fileUpload.filename:
# strip the leading path from the file name
fn = os.path.basename(fileUpload.filename)
# open read and write the file into the server
open(fn, 'wb').write(fileUpload.file.read())
# subprocess.check_output(
# [
# "./truepic",
# "sign",
# fileUpload.filename,
# "--output",
# (os.getcwd() + "/static/" + fileUpload.filename),
# ]
# )
#call steg sign script
response = subprocess.check_output(
[
"./scripts/verify.sh",
fileUpload.filename,
]
)
logging.warning(response)
return {"response": fileUpload.filename}
@app.post("/sign")
def sign_image(fileUpload: UploadFile):
logging.warning("in sign")
logging.warning(fileUpload.filename)
# check if the file has been uploaded
if fileUpload.filename:
# strip the leading path from the file name
fn = os.path.basename(fileUpload.filename)
# open read and write the file into the server
open(fn, 'wb').write(fileUpload.file.read())
# subprocess.check_output(
# [
# "./truepic",
# "sign",
# fileUpload.filename,
# "--output",
# (os.getcwd() + "/static/" + fileUpload.filename),
# ]
# )
#call steg sign script
response = subprocess.check_output(
[
"./scripts/sign.sh",
fileUpload.filename,
]
)
logging.warning(response)
return {"response": fileUpload.filename}
app.mount("/", StaticFiles(directory="static", html=True), name="static")
@app.get("/")
def index() -> FileResponse:
return FileResponse(path="/app/static/index.html", media_type="text/html")
|