.

app.py

@@ -4,21 +4,25 @@ from pathlib import Path
 from wrapper import run_pipeline_on_image
 from PIL import Image
 
-def process(file_obj):
-    if not file_obj:
-        return None, None, None, None, [], ""
+
+def process(file_path):
+    if not file_path:
+        return None, None, None, None, None, [], ""
+
     with tempfile.TemporaryDirectory() as tmpdir:
-        # file_obj is a dict when using gr.File(type="file")
-        src = Path(file_obj.name)
+        src = Path(file_path)
         ext = src.suffix.lstrip('.') or 'tif'
         img_path = Path(tmpdir) / f"input.{ext}"
+
         try:
+            # Copy raw uploaded bytes
             img_bytes = src.read_bytes()
             img_path.write_bytes(img_bytes)
         except Exception:
             # Fallback: save via PIL if direct copy fails
             Image.open(src).save(img_path)
 
+        # Run the full sorghum pipeline
         outputs = run_pipeline_on_image(str(img_path), tmpdir, save_artifacts=True)
 
         def load_pil(path_str):
@@ -36,22 +40,32 @@ def process(file_obj):
         overlay = load_pil(outputs.get('Overlay'))
         mask = load_pil(outputs.get('Mask'))
         size_img = load_pil(str(Path(tmpdir) / 'results/size.size_analysis.png'))
+
         # Texture LBP green path
         lbp_path = Path(tmpdir) / 'texture_output/lbp_green.png'
         texture_img = load_pil(str(lbp_path)) if lbp_path.exists() else None
+
+        # Vegetation indices
         order = ['NDVI', 'GNDVI', 'SAVI']
         gallery_items = [load_pil(outputs[k]) for k in order if k in outputs]
+
         stats_text = outputs.get('StatsText', '')
+
         return size_img, composite, mask, overlay, texture_img, gallery_items, stats_text
 
+
 with gr.Blocks() as demo:
     gr.Markdown("# 🌿 Automated Plant Analysis Demo")
-    gr.Markdown("Upload a sorghum plant image to compute and visualize composite, mask, overlay, texture (LBP), vegetation indices, and statistics.")
+    gr.Markdown("Upload a sorghum plant image (TIFF preferred) to compute and visualize composite, mask, overlay, texture (LBP), vegetation indices, and statistics.")
 
     with gr.Row():
         with gr.Column():
-            # Use gr.File instead of gr.Image so TIFF is preserved
-            inp = gr.File(type="file", file_types=[".tif", ".tiff", ".png", ".jpg"], label="Upload Image")
+            # Use File input to preserve raw TIFFs
+            inp = gr.File(
+                type="filepath",
+                file_types=[".tif", ".tiff", ".png", ".jpg"],
+                label="Upload Image"
+            )
             run = gr.Button("Run Pipeline", variant="primary")
 
     with gr.Row():
@@ -66,7 +80,11 @@ with gr.Blocks() as demo:
     gallery = gr.Gallery(label="Vegetation Indices", columns=3, height="auto")
     stats = gr.Textbox(label="Statistics", lines=4)
 
-    run.click(process, inputs=inp, outputs=[size_img, composite_img, mask_img, overlay_img, texture_img, gallery, stats])
+    run.click(
+        process,
+        inputs=inp,
+        outputs=[size_img, composite_img, mask_img, overlay_img, texture_img, gallery, stats]
+    )
 
 if __name__ == "__main__":
     demo.launch()