Update app.py

app.py

@@ -20,16 +20,6 @@ model_dir = snapshot_download(
     repo_id="srijaydeshpande/spadesegresnet"
 )
 
-def superimpose_images(image1, image2, alpha=0.5):
-    if image1 is None or image2 is None:
-        return "Please upload both images."
-    try:
-        image1 = image1.resize(image2.size)
-        blended = Image.blend(image1, image2, alpha)
-        return blended
-    except Exception as e:
-        return f"Error superimposing images: {str(e)}"
-
 class SPADE(nn.Module):
     def __init__(self, norm_nc, label_nc, norm):
         super().__init__()
@@ -276,7 +266,20 @@ def segment_image(image):
 
     legend = Image.open('legend.png')
 
-    return image, legend, stats
+    superimposed_image = superimpose_images(img, image)
+
+    return image, legend, stats, superimposed_image
+
+def superimpose_images(image1, image2, alpha=0.5):
+    if image1 is None or image2 is None:
+        return "Please upload both images."
+    try:
+        image1 = image1.resize(image2.size)
+        blended = Image.blend(image1, image2, alpha)
+        return blended
+    except Exception as e:
+        return f"Error superimposing images: {str(e)}"
+
 
 model_path = os.path.join(model_dir, 'spaderesnet.pt')
 model = SPADEResNet(input_nc=3, output_nc=6)
@@ -287,50 +290,13 @@ examples = [
     ["sample1.png"],
     ["sample2.png"]
 ]
-
-input1 = gr.Image()
-output1 = gr.Image()
-output2 = gr.Image()
-output3 = gr.Image()
-
-with gr.Blocks() as demo:
     
-    # demo = gr.Interface(
-        #     segment_image,
-        #     inputs=gr.Image(),
-        #     examples=examples,
-        #     outputs=["image", "image", "image"],
-        #     title="Breast Cancer Semantic Segmentation"
-        # )
-    
-    # Segmentation Section
-    segment_button = gr.Button("Segment Image")
-    segment_button.click(
-            segment_image,
-            inputs=input1,
-            # examples=examples,
-            outputs=[output1, output2, output3],
-            # title="Breast Cancer Semantic Segmentation"
-        )
-    
-    # Superimpose Section
-    gr.Markdown("### Superimpose Images")
-    
-    alpha_slider = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.1, label="Alpha (Transparency)")
-    superimpose_btn = gr.Button("Superimpose")
-    
-    superimpose_btn.click(
-        superimpose_images,
-        inputs=[input1, output1, alpha_slider],
-        outputs=output_image
-    )
-    
-# demo = gr.Interface(
-#     segment_image,
-#     inputs=gr.Image(),
-#     examples=examples,
-#     outputs=["image", "image", "image"],
-#     title="Breast Cancer Semantic Segmentation"
-# )
+demo = gr.Interface(
+    segment_image,
+    inputs=gr.Image(),
+    examples=examples,
+    outputs=["image", "image", "image", "image"],
+    title="Breast Cancer Semantic Segmentation"
+)
 
 demo.launch()