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Update app.py
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app.py
CHANGED
@@ -69,11 +69,10 @@ COLORS = [
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def process(query_img, state,
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cfg_path='configs/demo_b.py'):
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cfg = Config.fromfile(cfg_path)
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kp_src_np = np.array(state['kp_src']).copy().astype(np.float32)
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kp_src_np[:, 0] = kp_src_np[:,
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kp_src_np[:, 1] = kp_src_np[:,
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1] / 128. * cfg.model.encoder_config.img_size
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kp_src_np = np.flip(kp_src_np, 1).copy()
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kp_src_tensor = torch.tensor(kp_src_np).float()
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preprocess = transforms.Compose([
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@@ -83,7 +82,7 @@ def process(query_img, state,
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cfg.model.encoder_config.img_size)])
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if len(state['skeleton']) == 0:
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skeleton = [(0, 0)]
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support_img = preprocess(state['original_support_image']).flip(0)[None]
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np_query = np.array(query_img)[:, :, ::-1].copy()
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@@ -296,7 +295,8 @@ with gr.Blocks() as demo:
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state['skeleton'].clear()
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state['kp_src'].clear()
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state['original_support_image'] = np.array(support_img)[:, :, ::-1].copy()
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return support_img, support_img, state
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def process(query_img, state,
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cfg_path='configs/demo_b.py'):
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cfg = Config.fromfile(cfg_path)
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width, height, _ = state['original_support_image'].shape
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kp_src_np = np.array(state['kp_src']).copy().astype(np.float32)
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kp_src_np[:, 0] = kp_src_np[:,0] / (width // 2) * cfg.model.encoder_config.img_size
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kp_src_np[:, 1] = kp_src_np[:,1] / (height // 2) * cfg.model.encoder_config.img_size
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kp_src_np = np.flip(kp_src_np, 1).copy()
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kp_src_tensor = torch.tensor(kp_src_np).float()
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preprocess = transforms.Compose([
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cfg.model.encoder_config.img_size)])
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if len(state['skeleton']) == 0:
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state['skeleton'] = [(0, 0)]
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support_img = preprocess(state['original_support_image']).flip(0)[None]
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np_query = np.array(query_img)[:, :, ::-1].copy()
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state['skeleton'].clear()
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state['kp_src'].clear()
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state['original_support_image'] = np.array(support_img)[:, :, ::-1].copy()
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width, height = support_img.size
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support_img = support_img.resize((width // 2, width // 2), Image.Resampling.LANCZOS)
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return support_img, support_img, state
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