update

app.py

@@ -4,7 +4,7 @@ from pathlib import Path
 from wrapper import run_pipeline_on_image
 from PIL import Image
 
-
+##add the process function
 def process(file_path):
     if not file_path:
         return None, None, None, None, None, [], ""
@@ -57,7 +57,26 @@ def process(file_path):
 
         stats_text = outputs.get('StatsText', '')
 
-        return size_img, composite, mask, overlay, input_img, yolo_img, texture_img, hog_img, lac1_img, gallery_items, stats_text
+        # Output order matches UI components defined below
+        # Row 1: Input image (slightly larger)
+        # Row 2: Composite, Mask, Overlay
+        # Row 3: Texture images (LBP, HOG, Lac1)
+        # Row 4: Vegetation indices (gallery)
+        # Row 5: Morphology Size and YOLO Tips
+        # Final: Stats table
+        return (
+            input_img,
+            composite,
+            mask,
+            overlay,
+            texture_img,
+            hog_img,
+            lac1_img,
+            gallery_items,
+            size_img,
+            yolo_img,
+            stats_text,
+        )
 
 
 with gr.Blocks() as demo:
@@ -74,26 +93,49 @@ with gr.Blocks() as demo:
             )
             run = gr.Button("Run Pipeline", variant="primary")
 
+    # Row 1: input image, slightly larger
+    with gr.Row():
+        input_img = gr.Image(type="pil", label="Input Image", interactive=False, height=380)
+    # Row 2: composite, mask, overlay
     with gr.Row():
-        size_img = gr.Image(type="pil", label="Morphology Size", interactive=False)
         composite_img = gr.Image(type="pil", label="Composite (Segmentation Input)", interactive=False)
         mask_img = gr.Image(type="pil", label="Mask", interactive=False)
         overlay_img = gr.Image(type="pil", label="Segmentation Overlay", interactive=False)
-        input_img = gr.Image(type="pil", label="Input Image", interactive=False)
 
+    # Row 3: textures
     with gr.Row():
-        yolo_img = gr.Image(type="pil", label="YOLO Tips", interactive=False)
         texture_img = gr.Image(type="pil", label="Texture LBP (Green Band)", interactive=False)
         hog_img = gr.Image(type="pil", label="Texture HOG (Green Band)", interactive=False)
         lac1_img = gr.Image(type="pil", label="Texture Lac1 (Green Band)", interactive=False)
+    
+    # Row 4: vegetation indices
 
     gallery = gr.Gallery(label="Vegetation Indices", columns=3, height="auto")
+
+    # Row 5: morphology and YOLO tips
+    with gr.Row():
+        size_img = gr.Image(type="pil", label="Morphology Size", interactive=False)
+        yolo_img = gr.Image(type="pil", label="YOLO Tips", interactive=False)
+
+    # Final: statistics table
     stats = gr.Textbox(label="Statistics", lines=4)
 
     run.click(
         process,
         inputs=inp,
-        outputs=[size_img, composite_img, mask_img, overlay_img, input_img, yolo_img, texture_img, hog_img, lac1_img, gallery, stats]
+        outputs=[
+            input_img,
+            composite_img,
+            mask_img,
+            overlay_img,
+            texture_img,
+            hog_img,
+            lac1_img,
+            gallery,
+            size_img,
+            yolo_img,
+            stats,
+        ]
     )
 
 if __name__ == "__main__":

requirements.txt

@@ -1,3 +1,4 @@
+#all the requirements for the pipeline
 gradio
 pillow
 numpy
@@ -11,4 +12,5 @@ scipy
 matplotlib
 plantcv
 kornia
-timm
+timm
+ultralytics