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README.md
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license: mit
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---
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license: mit
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---
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# Background Removal
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[U-Net](https://arxiv.org/abs/1505.04597v1) Like([VGG](https://paperswithcode.com/method/vgg) Encoder) Pretrained Model For Human Body Detection ([pytorch](https://pytorch.org/), [Semantic Segmentation](https://paperswithcode.com/task/semantic-segmentation))
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#### **Quick Links**
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- [Implementation](#Implementation)
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- [Usage](#Usage)
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- [Examples](#Examples)
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## Implementation
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### VGG Encoder Implementation
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```python
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def VGGEncoder():
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weights = VGG16_Weights.DEFAULT
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base_model = vgg16(weights=weights)
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base_model.training = False
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encoder_seq = nn.ModuleList()
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moduls = nn.Sequential()
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for layer in list(base_model.features.children()):
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if isinstance(layer, nn.modules.pooling.MaxPool2d):
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encoder_seq.append(moduls)
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moduls = nn.Sequential()
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else:
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moduls.append(layer)
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return encoder_seq
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```
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## Usage:
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```python
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detector = BodyDetector("model_weights/bgrm-bh.pth")
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```
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Load model.
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```python
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fname = RandomSample("background folder", '*')
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bg = LoadImage(fname)
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```
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Read background image.
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```python
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fname = RandomSample("image folder")
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img = LoadImage(fname)
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img_resize = cv2.resize(img, (224, 224), interpolation = cv2.INTER_AREA)
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```
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Read image in bgr mode and resize it to 224*224.
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```python
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mask = detector.DetectBody(img_resize)
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```
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Detect object(human body) area.
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```python
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res = ReplaceBG(img, mask, bg)
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```
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Replace current background with loaded background image.
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