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handler.py

@@ -64,16 +64,25 @@ class EmotionCNN:
             from skimage.transform import resize
             mel_resized = resize(mel_spec_norm, (224, 224), mode="constant")
         except ImportError:
-            # Fallback: simple nearest-neighbor resize with numpy
-            mel_resized = np.array(
-                [np.interp(np.linspace(0, mel_spec_norm.shape[1]-1, 224),
-                           np.arange(mel_spec_norm.shape[1]), row)
-                 for row in np.interp(
-                     np.linspace(0, mel_spec_norm.shape[0]-1, 224),
-                     np.arange(mel_spec_norm.shape[0]),
-                     np.arange(mel_spec_norm.shape[0])
-                 ).astype(int).__iter__()]
-            ) if mel_spec_norm.size > 0 else np.zeros((224, 224))
+            # Fallback: resizing with numpy interpolation (nearest neighbor for rows, linear for cols)
+            target_h, target_w = 224, 224
+            source_h, source_w = mel_spec_norm.shape
+            
+            if source_h > 0 and source_w > 0:
+                # 1. Resize height (rows)
+                row_indices = np.linspace(0, source_h - 1, target_h).astype(int)
+                # Select rows (nearest neighbor)
+                temp = mel_spec_norm[row_indices, :]  
+                
+                # 2. Resize width (cols)
+                mel_resized = np.zeros((target_h, target_w), dtype=mel_spec_norm.dtype)
+                x_source = np.arange(source_w)
+                x_target = np.linspace(0, source_w - 1, target_w)
+                
+                for i in range(target_h):
+                    mel_resized[i, :] = np.interp(x_target, x_source, temp[i, :])
+            else:
+                mel_resized = np.zeros((224, 224))
 
         try:
             from matplotlib import cm

requirements.txt

@@ -15,3 +15,4 @@ fastapi==0.95.2
 uvicorn==0.22.0
 python-multipart==0.0.6
 huggingface_hub>=0.19.0
+scikit-image>=0.21.0