Create app.py

app.py

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+import gradio as gr
+import cv2
+import torch
+import numpy as np
+import matplotlib.pyplot as plt
+from celldetection import fetch_model, to_tensor
+
+device = 'cpu'
+model = fetch_model('ginoro_CpnResNeXt101UNet-fbe875f1a3e5ce2c').to(device).eval()
+
+def segment(image):
+    img_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) / 255.0
+    x = to_tensor(img_rgb, transpose=True, device=device, dtype=torch.float32)[None]
+    
+    with torch.no_grad():
+        output = model(x)
+    
+    contours = output['contours'][0]
+    original = (img_rgb * 255).astype(np.uint8).copy()
+    segmented = original.copy()
+    
+    for contour in contours:
+        contour = np.array(contour.cpu(), dtype=np.int32)
+        cv2.drawContours(segmented, [contour], -1, (0, 255, 0), 2)
+
+    h, w, c = original.shape
+    gap = 60
+    canvas = np.zeros((h, w * 2 + gap, c), dtype=np.uint8)
+    canvas[:, :w, :] = original
+    canvas[:, w + gap:, :] = segmented
+    return cv2.cvtColor(canvas, cv2.COLOR_RGB2BGR)
+
+gr.Interface(fn=segment, inputs=gr.Image(type="numpy"), outputs="image",
+             title="Cell Segmentation Demo (FZJ-INM1)",
+             description="Upload a microscopy image to see side-by-side segmentation.").launch()