update

app.py

@@ -20,9 +20,9 @@ def process(image):
         img_path = Path(tmpdir) / f"input.{ext}"
         image.save(img_path)
         outputs = run_pipeline_on_image(str(img_path), tmpdir, save_artifacts=True)
-        # Keep order consistent: return exactly the 7 images
+        # Keep order consistent: return vegetation indices only for now
         order = [
-            'NDVI', 'ARI', 'GNDVI', 'LBP', 'HOG', 'Lacunarity', 'SizeAnalysis'
+            'NDVI', 'ARI', 'GNDVI'  # , 'LBP', 'HOG', 'Lacunarity', 'SizeAnalysis'
         ]
         return [outputs[k] for k in order if k in outputs]
 

sorghum_pipeline/pipeline.py

@@ -88,17 +88,18 @@ class SorghumPipeline:
         return plants
     
     def _extract_features(self, plants: Dict[str, Any]) -> Dict[str, Any]:
-        """Extract texture, vegetation, and morphology features."""
+        """Extract features (NDVI only for now)."""
         for key, pdata in plants.items():
-            # Texture: LBP, HOG, Lacunarity from pseudo-color
             composite = pdata['composite']
             mask = pdata.get('mask')
-            masked = self.mask_handler.apply_mask_to_image(composite, mask) if mask is not None else composite
-            gray = cv2.cvtColor(masked, cv2.COLOR_BGR2GRAY)
             
-            feats = self.texture_extractor.extract_all_texture_features(gray)
-            stats = self.texture_extractor.compute_texture_statistics(feats, mask)
-            pdata['texture_features'] = {'color': {'features': feats, 'statistics': stats}}
+            # # Texture: LBP, HOG, Lacunarity from pseudo-color (COMMENTED OUT)
+            # masked = self.mask_handler.apply_mask_to_image(composite, mask) if mask is not None else composite
+            # gray = cv2.cvtColor(masked, cv2.COLOR_BGR2GRAY)
+            # feats = self.texture_extractor.extract_all_texture_features(gray)
+            # stats = self.texture_extractor.compute_texture_statistics(feats, mask)
+            # pdata['texture_features'] = {'color': {'features': feats, 'statistics': stats}}
+            pdata['texture_features'] = {}
             
             # Vegetation: NDVI, ARI, GNDVI
             spectral = pdata.get('spectral_stack', {})
@@ -107,8 +108,9 @@ class SorghumPipeline:
             else:
                 pdata['vegetation_indices'] = {}
             
-            # Morphology: PlantCV size analysis
-            pdata['morphology_features'] = self.morphology_extractor.extract_morphology_features(composite, mask)
+            # # Morphology: PlantCV size analysis (COMMENTED OUT)
+            # pdata['morphology_features'] = self.morphology_extractor.extract_morphology_features(composite, mask)
+            pdata['morphology_features'] = {}
         
         return plants
     

wrapper.py

@@ -38,18 +38,18 @@ def run_pipeline_on_image(input_image_path: str, work_dir: str, save_artifacts:
     # Collect outputs
     outputs: Dict[str, str] = {}
 
-    # Return only the requested 7 images with fixed keys
+    # Return only NDVI for now (others commented out for debugging)
     wanted = [
         work / 'Vegetation_indices_images/ndvi.png',
         work / 'Vegetation_indices_images/ari.png',
         work / 'Vegetation_indices_images/gndvi.png',
-        work / 'texture_output/lbp.png',
-        work / 'texture_output/hog.png',
-        work / 'texture_output/lacunarity.png',
-        work / 'results/size.size_analysis.png',
+        # work / 'texture_output/lbp.png',
+        # work / 'texture_output/hog.png',
+        # work / 'texture_output/lacunarity.png',
+        # work / 'results/size.size_analysis.png',
     ]
     labels = [
-        'NDVI', 'ARI', 'GNDVI', 'LBP', 'HOG', 'Lacunarity', 'SizeAnalysis'
+        'NDVI', 'ARI', 'GNDVI',  # 'LBP', 'HOG', 'Lacunarity', 'SizeAnalysis'
     ]
     for label, path in zip(labels, wanted):
         if path.exists():