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app.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[6]:
+
+
+import os
+import cv2
+import paddlehub as hub
+import gradio as gr
+import torch
+import urllib.request
+
+
+# In[7]:
+
+
+# Fetch image for analysis
+img_url = "http://claireye.com.tw/img/230212a.jpg"
+urllib.request.urlretrieve(img_url, "pose.jpg")
+model = hub.Module(name='U2Net')
+
+
+# In[8]:
+
+
+def infer(webcam, img,option):
+  if option == "webcam":
+      webcam.save('temp.jpg')
+      result = model.Segmentation(
+          images=[cv2.imread("temp.jpg")],
+          paths=None,
+          batch_size=1,
+          input_size=320,
+          output_dir='output',
+          visualization=True)
+  else:
+      img.save('temp.jpg')
+      result = model.Segmentation(
+          images=[cv2.imread("temp.jpg")],
+          paths=None,
+          batch_size=1,
+          input_size=320,
+          output_dir='output',
+          visualization=True)
+  return result[0]['front'][:,:,::-1], result[0]['mask']
+
+
+# In[9]:
+
+
+inputs = [gr.inputs.Image(source="webcam", label="Webcam", type="pil",optional=True),gr.inputs.Image(source="upload", label="Input Image", type="pil",optional=True),gr.inputs.Radio(choices=["webcam","Image"], type="value", default="Image", label="Input Type")]
+outputs = [
+           gr.outputs.Image(type="numpy",label="Front"),
+           gr.outputs.Image(type="numpy",label="Mask")
+           ]
+
+title = "U^2-Net"
+description = "demo for U^2-Net. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='http://claireye.com.tw'>Claireye</a> | 2023</p>"
+examples = [
+  ['pose.jpg','pose.jpg','Image'],
+]
+
+
+# In[10]:
+
+
+gr.Interface(infer, inputs, outputs, title=title, description=description, article=article, examples=examples).launch()
+
+
+# In[ ]:
+
+
+
+

requirements.txt

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+numpy
+scikit-image
+torch
+torchvision
+pillow
+opencv-python-headless
+paddlepaddle
+paddlehub
+gradio