philschmid HF staff commited on
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a0e9111
1 Parent(s): f717c2a

Upload 11 files (#1)

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- Upload 11 files (6402e73fcb3b72796de40f3d5936967fe92b5b69)
- Update requirements.txt (716062eb782ef9a0f1299544cde847f84f86fe51)

Files changed (6) hide show
  1. README.md +15 -10
  2. create_handler.ipynb +0 -0
  3. crysis.jpeg +0 -0
  4. requirements.txt +0 -1
  5. result_crysis.png +0 -0
  6. thumbnail.png +0 -0
README.md CHANGED
@@ -35,7 +35,6 @@ There is also a [notebook](https://huggingface.co/philschmid/ControlNet-endpoint
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  "negative_prompt": "low res, bad anatomy, worst quality, low quality",
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  "controlnet_type": "depth",
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  "image" : "iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAIAAAB7GkOtAAAABGdBTUEAALGPC",
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- "mask_image": "iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAIAAAB7GkOtAAAABGdBTUEAALGPC",
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  }
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  ```
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@@ -61,8 +60,8 @@ import base64
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  from PIL import Image
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  from io import BytesIO
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- ENDPOINT_URL = ""
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- HF_TOKEN = ""
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  # helper image utils
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  def encode_image(image_path):
@@ -73,10 +72,9 @@ def encode_image(image_path):
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  def predict(prompt, image, negative_prompt=None, controlnet_type = "normal"):
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  image = encode_image(image)
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- mask_image = encode_image(mask_image)
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  # prepare sample payload
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- request = {"prompt": prompt, "image": image, "negative_prompt": negative_prompt, "controlnet_type": controlnet_type}
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  # headers
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  headers = {
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  "Authorization": f"Bearer {HF_TOKEN}",
@@ -84,17 +82,24 @@ def predict(prompt, image, negative_prompt=None, controlnet_type = "normal"):
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  "Accept": "image/png" # important to get an image back
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  }
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- response = r.post(ENDPOINT_URL, headers=headers, json=payload)
 
 
 
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  img = Image.open(BytesIO(response.content))
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  return img
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  prediction = predict(
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- prompt = "best quality, extremely detailed",
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- negative_prompt ="lowres, bad anatomy, worst quality, low quality",
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- controlnet_type = "depth",
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- image = encode_image("input_image_vermeer.png")
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  )
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  ```
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  expected output
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  "negative_prompt": "low res, bad anatomy, worst quality, low quality",
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  "controlnet_type": "depth",
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  "image" : "iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAIAAAB7GkOtAAAABGdBTUEAALGPC",
 
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  }
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  ```
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  from PIL import Image
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  from io import BytesIO
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+ ENDPOINT_URL = "" # your endpoint url
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+ HF_TOKEN = "" # your huggingface token `hf_xxx`
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  # helper image utils
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  def encode_image(image_path):
 
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  def predict(prompt, image, negative_prompt=None, controlnet_type = "normal"):
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  image = encode_image(image)
 
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  # prepare sample payload
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+ request = {"inputs": prompt, "image": image, "negative_prompt": negative_prompt, "controlnet_type": controlnet_type}
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  # headers
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  headers = {
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  "Authorization": f"Bearer {HF_TOKEN}",
 
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  "Accept": "image/png" # important to get an image back
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  }
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+ response = r.post(ENDPOINT_URL, headers=headers, json=request)
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+ if response.status_code != 200:
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+ print(response.text)
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+ raise Exception("Prediction failed")
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  img = Image.open(BytesIO(response.content))
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  return img
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+
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  prediction = predict(
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+ prompt = "cloudy sky background lush landscape house and green trees, RAW photo (high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, film grain, Fujifilm XT3",
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+ negative_prompt ="lowres, bad anatomy, worst quality, low quality, city, traffic",
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+ controlnet_type = "hed",
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+ image = "huggingface.png"
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  )
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+ prediction.save("result.png")
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+ ```
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+
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  ```
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  expected output
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create_handler.ipynb CHANGED
The diff for this file is too large to render. See raw diff
 
crysis.jpeg ADDED
requirements.txt CHANGED
@@ -1,6 +1,5 @@
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  git+https://github.com/huggingface/diffusers.git
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  safetensors
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- #xformers
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  opencv-python
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  controlnet_hinter==0.0.5
 
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  git+https://github.com/huggingface/diffusers.git
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  safetensors
 
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  opencv-python
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  controlnet_hinter==0.0.5
result_crysis.png CHANGED
thumbnail.png CHANGED