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.github/workflows/check_file_size.yml ADDED
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+ name: Check file size
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+ on: # or directly `on: [push]` to run the action on every push on any branch
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+ pull_request:
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+ branches: [main]
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+
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+ # to run this workflow manually from the Actions tab
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+ workflow_dispatch:
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+
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+ jobs:
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+ sync-to-hub:
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+ runs-on: ubuntu-latest
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+ steps:
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+ - name: Check large files
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+ uses: ActionsDesk/lfs-warning@v2.0
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+ with:
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+ filesizelimit: 10485760 # this is 10MB so we can sync to HF Spaces
.github/workflows/sync_to_huggingface.yml ADDED
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+ name: Sync to Hugging Face hub
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+ on:
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+ push:
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+ branches: [main]
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+
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+ # to run this workflow manually from the Actions tab
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+ workflow_dispatch:
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+
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+ jobs:
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+ sync-to-hub:
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+ runs-on: ubuntu-latest
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+ steps:
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+ - uses: actions/checkout@v3
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+ with:
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+ fetch-depth: 0
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+ - name: Push to hub
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+ env:
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+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
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+ run: git push --force https://alaaawad:$HF_TOKEN@huggingface.co/spaces/alaaawad/CLIPSeg_x_SD main
.gitignore ADDED
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+ *.pth
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+ # Jupyter Notebook
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+ .ipynb_checkpoints
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+
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+ # IPython
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+ profile_default/
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+ ipython_config.py
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+
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+ # pyenv
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+ # For a library or package, you might want to ignore these files since the code is
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+ # intended to run in multiple environments; otherwise, check them in:
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+ # .python-version
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+ # pipenv
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+ # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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+ .pdm.toml
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+ __pypackages__/
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+ # Celery stuff
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+ # Environments
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+ #.idea/
LICENSE ADDED
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+ MIT License
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+
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+ Copyright (c) 2022 Alaa
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+
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+ Permission is hereby granted, free of charge, to any person obtaining a copy
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+ of this software and associated documentation files (the "Software"), to deal
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+ in the Software without restriction, including without limitation the rights
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+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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+ copies of the Software, and to permit persons to whom the Software is
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+ furnished to do so, subject to the following conditions:
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+
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+ The above copyright notice and this permission notice shall be included in all
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+ copies or substantial portions of the Software.
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+
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+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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+ SOFTWARE.
README.md ADDED
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+ ---
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+ title: CLIPSeg X SD
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+ emoji: πŸ“‰
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+ colorFrom: yellow
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+ colorTo: gray
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+ sdk: gradio
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+ sdk_version: 3.12.0
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+ app_file: app.py
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+ pinned: false
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+ license: mit
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+ ---
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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+
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+
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+ It takes 3 mandatory inputs.
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+
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+ Input Image URL
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+ Prompt of the part in the input image that you want to replace
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+ Output Prompt
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+ There are certain parameters that you can tune
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+
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+ Mask Precision
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+ Stable Diffusion Generation Strength
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+
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+
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+
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+ Prerequisites:
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+ * GPU (runs fine on Google Colab Tesla T4)
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+
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+
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+ Clipseg Model Weights - https://github.com/timojl/clipseg
app.py ADDED
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+ from transformers import CLIPSegProcessor, CLIPSegForImageSegmentation
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+ import gradio as gr
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+ from PIL import Image
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+ import torch
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+ import matplotlib.pyplot as plt
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+ import cv2
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+
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+ processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
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+ model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
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+
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+ def process_image(image, prompt):
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+ inputs = processor(text=prompt, images=image, padding="max_length", return_tensors="pt")
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+
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+ # predict
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+ with torch.no_grad():
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+ outputs = model(**inputs)
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+ preds = outputs.logits
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+
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+ filename = f"mask.png"
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+ plt.imsave(filename, torch.sigmoid(preds))
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+ return Image.open("mask.png").convert("RGB")
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+
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+
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+
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+ title = "Interactive demo: zero-shot image segmentation with CLIPSeg"
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+
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+ description = "Demo for using CLIPSeg, a CLIP-based model for zero- and one-shot image segmentation. To use it, simply upload an image and add a text to mask (identify in the image), or use one of the examples below and click 'submit'. Results will show up in a few seconds."
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+
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+ article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2112.10003'>CLIPSeg: Image Segmentation Using Text and Image Prompts</a> | <a href='https://huggingface.co/docs/transformers/main/en/model_doc/clipseg'>HuggingFace docs</a></p>"
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+
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+ interface = gr.Interface(fn=process_image,
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+ inputs=[gr.Image(type="pil"), gr.Textbox(label="Please describe what you want to identify")],
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+ outputs=gr.Image(type="pil"),
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+ title=title,
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+ description=description,
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+ article=article)
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+
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+ interface.launch(debug=True)
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+
packages.txt ADDED
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+ python3-opencv
requirements.txt ADDED
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+ git+https://github.com/huggingface/transformers.git
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+ accelerate
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+ git+https://github.com/huggingface/diffusers.git
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+ torch
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+ opencv-python