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Update app.py
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app.py
CHANGED
@@ -310,7 +310,7 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
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return image
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def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, lora_repo_name):
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# get the lora and its
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lora = getLoraByRepoName(lora_repo_name)
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default_values = getLoraDefaultsByRepoName(lora_repo_name)
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@@ -319,6 +319,11 @@ def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_stre
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face_image = readb64(face_image)
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face_image = center_crop_image_as_square(face_image)
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try:
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face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))
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face_info = sorted(face_info, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])[-1] # only use the maximum face
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return image
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def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, lora_repo_name):
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# get the lora and its default values
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lora = getLoraByRepoName(lora_repo_name)
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default_values = getLoraDefaultsByRepoName(lora_repo_name)
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face_image = readb64(face_image)
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face_image = center_crop_image_as_square(face_image)
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# this is temporary, just to debug
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return writeb64(face_image)
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try:
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face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))
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face_info = sorted(face_info, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])[-1] # only use the maximum face
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