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fix typos

pull/202/head
ResearcherXman 2024-02-26 14:23:45 +08:00
parent 8413732ea1
commit 3437464e23
6 changed files with 6 additions and 11 deletions
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2
README.md
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@ -144,7 +144,7 @@ face_image = load_image("./examples/yann-lecun_resize.jpg")
# prepare face emb
face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))
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
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
face_emb = face_info['embedding']
face_kps = draw_kps(face_image, face_info['kps'])

7
gradio_demo/app-multicontrolnet.py
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@ -357,12 +357,7 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
f"Unable to detect a face in the image. Please upload a different photo with a clear face."
)
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
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
face_emb = face_info["embedding"]
face_kps = draw_kps(convert_from_cv2_to_image(face_image_cv2), face_info["kps"])
img_controlnet = face_image

2
gradio_demo/app.py
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@ -239,7 +239,7 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
if len(face_info) == 0:
raise gr.Error(f"Cannot find any face in the image! Please upload another person image")
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
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
face_emb = face_info['embedding']
face_kps = draw_kps(convert_from_cv2_to_image(face_image_cv2), face_info['kps'])

2
infer.py
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@ -64,7 +64,7 @@ if __name__ == "__main__":
face_image = resize_img(face_image)
face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))
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
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
face_emb = face_info['embedding']
face_kps = draw_kps(face_image, face_info['kps'])

4
infer_full.py
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@ -79,7 +79,7 @@ if __name__ == "__main__":
face_image = resize_img(face_image)
face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))
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
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
face_emb = face_info['embedding']
# use another reference image
@ -88,7 +88,7 @@ if __name__ == "__main__":
face_info = app.get(cv2.cvtColor(np.array(pose_image), cv2.COLOR_RGB2BGR))
pose_image_cv2 = convert_from_image_to_cv2(pose_image)
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
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
face_kps = draw_kps(pose_image, face_info['kps'])
width, height = face_kps.size