Add example images and enable Gradio examples

app.py

@@ -5,20 +5,22 @@ import numpy as np
 import matplotlib.pyplot as plt
 from celldetection import fetch_model, to_tensor
 
+# ✅ Load the model
 device = 'cpu'
 model = fetch_model('ginoro_CpnResNeXt101UNet-fbe875f1a3e5ce2c').to(device).eval()
 
+# ✅ Inference function
 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, (255, 0, 0), 2)
@@ -28,8 +30,22 @@ def segment(image):
     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()
+# ✅ Example images list
+examples = [
+    ["examples/1.png"],
+    ["examples/2.png"],
+    ["examples/3.png"]
+]
+
+# ✅ Launch the Gradio interface
+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.",
+    examples=examples
+).launch()

requirements.txt

@@ -1,5 +1,6 @@
 gradio
-torch
+opencv-python
 celldetection
-opencv-python-headless
+torch
+numpy
 matplotlib