update

app.py

@@ -2,13 +2,39 @@ import gradio as gr
 import tempfile
 from pathlib import Path
 from wrapper import run_pipeline_on_image
+import numpy as np
+from PIL import Image
+from itertools import product
 
 def show_preview(image):
-    """Show the original uploaded image as-is."""
+    """Show pseudo-RGB composite preview."""
     if image is None:
         return None
-    # Return original image without conversion
-    return image
+    
+    try:
+        # Process to pseudo-RGB composite (same as pipeline does)
+        d = image.size[0] // 2
+        boxes = [(j, i, j + d, i + d) for i, j in product(range(0, image.height, d), range(0, image.width, d))]
+        stack = np.stack([np.array(image.crop(box), dtype=float) for box in boxes], axis=-1)
+        green, red, red_edge, nir = np.split(stack, 4, axis=-1)
+        
+        # Pseudo-RGB: (green, red_edge, red)
+        composite = np.concatenate([green, red_edge, red], axis=-1)
+        
+        # Normalize to uint8
+        composite = np.nan_to_num(composite, nan=0.0, posinf=0.0, neginf=0.0)
+        ptp = np.ptp(composite)
+        if ptp > 0:
+            normalized = (composite - composite.min()) / (ptp + 1e-6) * 255
+        else:
+            normalized = np.zeros_like(composite)
+        composite_uint8 = np.clip(normalized, 0, 255).astype(np.uint8)
+        
+        # Convert to PIL for display
+        return Image.fromarray(composite_uint8)
+    except Exception as e:
+        # Fallback: return original if processing fails
+        return image
 
 def process(image):
     if image is None:

sorghum_pipeline/data/preprocessor.py

@@ -15,8 +15,9 @@ class ImagePreprocessor:
     def convert_to_uint8(self, arr: np.ndarray) -> np.ndarray:
         """Convert to uint8."""
         arr = np.nan_to_num(arr, nan=0.0, posinf=0.0, neginf=0.0)
-        if arr.ptp() > 0:
-            normalized = (arr - arr.min()) / (arr.ptp() + 1e-6) * 255
+        ptp = np.ptp(arr)
+        if ptp > 0:
+            normalized = (arr - arr.min()) / (ptp + 1e-6) * 255
         else:
             normalized = np.zeros_like(arr)
         return np.clip(normalized, 0, 255).astype(np.uint8)

sorghum_pipeline/features/texture.py

@@ -75,8 +75,9 @@ class TextureExtractor:
     def _convert_to_uint8(self, arr: np.ndarray) -> np.ndarray:
         """Convert to uint8."""
         arr = np.nan_to_num(arr, nan=0.0, posinf=0.0, neginf=0.0)
-        if arr.ptp() > 0:
-            normalized = (arr - arr.min()) / (arr.ptp() + 1e-6) * 255
+        ptp = np.ptp(arr)
+        if ptp > 0:
+            normalized = (arr - arr.min()) / (ptp + 1e-6) * 255
         else:
             normalized = np.zeros_like(arr)
         return np.clip(normalized, 0, 255).astype(np.uint8)

sorghum_pipeline/output/manager.py

@@ -136,8 +136,9 @@ class OutputManager:
     def _normalize_to_uint8(self, arr: np.ndarray) -> np.ndarray:
         """Normalize to uint8."""
         arr = np.nan_to_num(arr, nan=0.0, posinf=0.0, neginf=0.0)
-        if arr.ptp() > 0:
-            normalized = (arr - arr.min()) / (arr.ptp() + 1e-6) * 255
+        ptp = np.ptp(arr)
+        if ptp > 0:
+            normalized = (arr - arr.min()) / (ptp + 1e-6) * 255
         else:
             normalized = np.zeros_like(arr)
         return np.clip(normalized, 0, 255).astype(np.uint8)