:beers: cheers

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.github/workflows/check_size.yaml

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+name: Check file size
+
+on:
+  pull_request:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check large files
+        uses: ActionsDesk/lfs-warning@v2.0
+        with:
+          filesizelimit: 10485760 # = 10MB, so we can sync to HF spaces

.github/workflows/sync_to_hub.yaml

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+name: Sync to Hugging Face hub
+
+on:
+  push:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+      - name: Push to hub
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: git push https://nateraw:$HF_TOKEN@huggingface.co/spaces/nateraw/background-remover main --force

README.md

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+---
+title: background-remover
+emoji: 🤗
+colorFrom: blue
+colorTo: red
+sdk: gradio
+app_file: app.py
+pinned: false
+---
+
+# background-remover
+
+[![Generic badge](https://img.shields.io/badge/🤗-Open%20In%20Spaces-blue.svg)](https://huggingface.co/spaces/nateraw/background-remover)
+
+A Gradio app to remove the background from an image
+
+---
+
+Autogenerated using [this template](https://github.com/nateraw/spaces-template)

app.py

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+import cv2
+import gradio as gr
+import numpy as np
+import onnxruntime
+from huggingface_hub import hf_hub_download
+from PIL import Image
+
+
+# Get x_scale_factor & y_scale_factor to resize image
+def get_scale_factor(im_h, im_w, ref_size=512):
+
+    if max(im_h, im_w) < ref_size or min(im_h, im_w) > ref_size:
+        if im_w >= im_h:
+            im_rh = ref_size
+            im_rw = int(im_w / im_h * ref_size)
+        elif im_w < im_h:
+            im_rw = ref_size
+            im_rh = int(im_h / im_w * ref_size)
+    else:
+        im_rh = im_h
+        im_rw = im_w
+
+    im_rw = im_rw - im_rw % 32
+    im_rh = im_rh - im_rh % 32
+
+    x_scale_factor = im_rw / im_w
+    y_scale_factor = im_rh / im_h
+
+    return x_scale_factor, y_scale_factor
+
+
+MODEL_PATH = hf_hub_download('nateraw/background-remover-files', 'modnet.onnx', repo_type='dataset')
+
+
+def main(image_path):
+
+    # read image
+    im = cv2.imread(image_path)
+    im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
+
+    # unify image channels to 3
+    if len(im.shape) == 2:
+        im = im[:, :, None]
+    if im.shape[2] == 1:
+        im = np.repeat(im, 3, axis=2)
+    elif im.shape[2] == 4:
+        im = im[:, :, 0:3]
+
+    # normalize values to scale it between -1 to 1
+    im = (im - 127.5) / 127.5
+
+    im_h, im_w, im_c = im.shape
+    x, y = get_scale_factor(im_h, im_w)
+
+    # resize image
+    im = cv2.resize(im, None, fx=x, fy=y, interpolation=cv2.INTER_AREA)
+
+    # prepare input shape
+    im = np.transpose(im)
+    im = np.swapaxes(im, 1, 2)
+    im = np.expand_dims(im, axis=0).astype('float32')
+
+    # Initialize session and get prediction
+    session = onnxruntime.InferenceSession(MODEL_PATH, None)
+    input_name = session.get_inputs()[0].name
+    output_name = session.get_outputs()[0].name
+    result = session.run([output_name], {input_name: im})
+
+    # refine matte
+    matte = (np.squeeze(result[0]) * 255).astype('uint8')
+    matte = cv2.resize(matte, dsize=(im_w, im_h), interpolation=cv2.INTER_AREA)
+
+    # HACK - Could probably just convert this to PIL instead of writing
+    cv2.imwrite('out.png', matte)
+
+    image = Image.open(image_path)
+    matte = Image.open('out.png')
+
+    # obtain predicted foreground
+    image = np.asarray(image)
+    if len(image.shape) == 2:
+        image = image[:, :, None]
+    if image.shape[2] == 1:
+        image = np.repeat(image, 3, axis=2)
+    elif image.shape[2] == 4:
+        image = image[:, :, 0:3]
+    matte = np.repeat(np.asarray(matte)[:, :, None], 3, axis=2) / 255
+    foreground = image * matte + np.full(image.shape, 255) * (1 - matte)
+    return Image.fromarray(foreground.astype(np.uint8))
+
+
+title = "MODNet Background Remover"
+description = "Gradio demo for MODNet, a model that can remove the background from a given image. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
+article = "<div style='text-align: center;'> <a href='https://github.com/ZHKKKe/MODNet' target='_blank'>Github Repo</a> | <a href='https://arxiv.org/abs/2011.11961' target='_blank'>MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition</a> </div>"
+
+interface = gr.Interface(
+    fn=main,
+    inputs=gr.inputs.Image(type='filepath'),
+    outputs='image',
+    examples=[
+        [
+            hf_hub_download(
+                'nateraw/background-remover-files',
+                'twitter_profile_pic.jpeg',
+                repo_type='dataset',
+                force_filename='twitter_profile_pic.jpeg',
+            )
+        ]
+    ],
+    title=title,
+    description=description,
+    article=article,
+)
+
+if __name__ == '__main__':
+    interface.launch(debug=True)

packages.txt

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+ffmpeg 
+libsm6 
+libxext6

requirements.txt

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+gradio
+onnxruntime==1.6.0
+onnx
+opencv-python
+numpy
+huggingface_hub