yuragoithf commited on
Commit
7e182e3
1 Parent(s): 14f2a96

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +13 -2
app.py CHANGED
@@ -56,6 +56,16 @@ inputs = gr.inputs.Image(type="pil", label="Upload an image", source="upload")
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  image_output = gr.outputs.Image(type="numpy", label="Output Image")
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  # outputs = gr.outputs.HTML() #uncomment for single class output
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  def gen_pred(img=inputs, model=seg_model):
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  # rgb_path = os.path.join(test_image_dir,img)
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  # img = cv2.imread(rgb_path)
@@ -69,11 +79,12 @@ def gen_pred(img=inputs, model=seg_model):
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  pred = model.predict(img)
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  pred = np.squeeze(pred, axis=0)
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  print(pred)
 
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  # color_coverted = cv2.cvtColor(pred, cv2.COLOR_BGR2RGB)
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  # pil_image = Image.fromarray(pred)
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- PIL_image = Image.fromarray(pred.astype('uint8'), 'RGB')
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  # return "UI in developing process ..."
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- return PIL_image
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  title = "<h1 style='text-align: center;'>Semantic Segmentation</h1>"
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  description = "Upload an image and get prediction mask"
 
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  image_output = gr.outputs.Image(type="numpy", label="Output Image")
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  # outputs = gr.outputs.HTML() #uncomment for single class output
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+ def fig2img(fig):
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+ """Convert a Matplotlib figure to a PIL Image and return it"""
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+ import io
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+ buf = io.BytesIO()
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+ fig.savefig(buf)
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+ buf.seek(0)
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+ img = Image.open(buf)
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+ return img
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+
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+
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  def gen_pred(img=inputs, model=seg_model):
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  # rgb_path = os.path.join(test_image_dir,img)
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  # img = cv2.imread(rgb_path)
 
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  pred = model.predict(img)
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  pred = np.squeeze(pred, axis=0)
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  print(pred)
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+ pred = fig2img(pred)
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  # color_coverted = cv2.cvtColor(pred, cv2.COLOR_BGR2RGB)
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  # pil_image = Image.fromarray(pred)
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+ # PIL_image = Image.fromarray(pred.astype('uint8'), 'RGB')
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  # return "UI in developing process ..."
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+ return pred
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  title = "<h1 style='text-align: center;'>Semantic Segmentation</h1>"
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  description = "Upload an image and get prediction mask"