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Runtime error
Hanxiao Xiang
commited on
Commit
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4d77be5
1
Parent(s):
49f5d1a
Update app.py
Browse files
app.py
CHANGED
@@ -1,10 +1,10 @@
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import subprocess
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subprocess.call("mim install 'mmengine>=0.6.0'", shell=True)
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subprocess.call("mim install 'mmcv>=2.0.0rc4,<2.1.0'", shell=True)
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subprocess.call("min install 'mmdet>=3.0.0,<4.0.0'", shell=True)
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subprocess.call("mim install 'mmyolo'", shell=True)
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subprocess.call("mim install 'mmpose'", shell=True)
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subprocess.call("mim install 'mmpretrain'", shell=True)
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import numpy as np
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import gradio as gr
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@@ -61,7 +61,7 @@ def get_access_token(refatch=False) -> str:
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return access_token
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def resize_image(img, max_length=
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"""Ensure that the longest side is shorter than 524px and the shortest side is longer than 50px.
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:param img: 前端传入的图片
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:param max_length: 最长边像素
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@@ -196,7 +196,7 @@ def model2_rem(x):
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return new_img, resized_f
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def model3_ext(x: np.ndarray, num_clusters=
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"""主色调提取
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:param x: 前端传入的图片
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:param num_clusters: 聚类的数量
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@@ -329,7 +329,7 @@ with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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model3_input = gr.Image(height=400, image_mode='RGBA')
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model3_slider = gr.Slider(minimum=1, maximum=20, step=1, value=
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min_width=400, label="聚类数量")
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with gr.Column():
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model3_output_img = gr.Image(height=100)
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# import subprocess
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# subprocess.call("mim install 'mmengine>=0.6.0'", shell=True)
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# subprocess.call("mim install 'mmcv>=2.0.0rc4,<2.1.0'", shell=True)
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# subprocess.call("min install 'mmdet>=3.0.0,<4.0.0'", shell=True)
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# subprocess.call("mim install 'mmyolo'", shell=True)
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# subprocess.call("mim install 'mmpose'", shell=True)
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# subprocess.call("mim install 'mmpretrain'", shell=True)
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import numpy as np
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import gradio as gr
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return access_token
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def resize_image(img, max_length=2048, min_length=50) -> Tuple[np.ndarray, bool]:
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"""Ensure that the longest side is shorter than 524px and the shortest side is longer than 50px.
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:param img: 前端传入的图片
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:param max_length: 最长边像素
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return new_img, resized_f
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def model3_ext(x: np.ndarray, num_clusters=8):
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"""主色调提取
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:param x: 前端传入的图片
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:param num_clusters: 聚类的数量
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with gr.Row():
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with gr.Column():
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model3_input = gr.Image(height=400, image_mode='RGBA')
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model3_slider = gr.Slider(minimum=1, maximum=20, step=1, value=8,
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min_width=400, label="聚类数量")
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with gr.Column():
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model3_output_img = gr.Image(height=100)
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