Removed redundant validation

yolo_predictor.py

@@ -13,69 +13,6 @@ def load_yolo_model(model_path):
     """Load YOLO model from .pt file"""
     return YOLO(model_path)
 
-def validate_4channel_tiff(image_path):
-    """
-    Validate that the input TIFF file has 4 channels and is readable
-    
-    Args:
-        image_path: Path to input TIFF image
-    
-    Returns:
-        bool: True if valid 4-channel TIFF
-        
-    Raises:
-        ValueError: If validation fails
-    """
-    if not os.path.exists(image_path):
-        logger.error(f"Image file does not exist: {image_path}")
-        raise ValueError(f"Image file does not exist: {image_path}")
-    
-    logger.info(f"Validating TIFF file: {image_path}")
-    
-    try:
-        # Primary validation with tifffile
-        img_array = tifffile.imread(image_path)
-        
-        # Check array shape and channels
-        if len(img_array.shape) == 3:
-            if img_array.shape[0] == 4:
-                # Shape is (4, H, W)
-                channels = 4
-                height, width = img_array.shape[1], img_array.shape[2]
-            elif img_array.shape[2] == 4:
-                # Shape is (H, W, 4)
-                channels = 4
-                height, width = img_array.shape[0], img_array.shape[1]
-            else:
-                channels = min(img_array.shape[0], img_array.shape[2])
-                height, width = img_array.shape[0], img_array.shape[1]
-        else:
-            logger.error(f"Invalid image shape: {img_array.shape}. Expected 3D array with 4 channels.")
-            raise ValueError(f"Invalid image shape: {img_array.shape}. Expected 3D array with 4 channels.")
-            
-        if channels != 4:
-            logger.error(f"YOLO model expects 4-channel images, but got {channels} channels")
-            raise ValueError(f"YOLO model expects 4-channel images, but got {channels} channels")
-            
-        logger.info(f"Validation successful: {channels} channels, {height}x{width}, dtype: {img_array.dtype}")
-        return True
-        
-    except Exception as e:
-        logger.warning(f"Tifffile validation failed: {str(e)}, trying rasterio fallback")
-        # Fallback validation with rasterio
-        try:
-            with rasterio.open(image_path) as src:
-                if src.count != 4:
-                    logger.error(f"YOLO model expects 4-channel images, but got {src.count} channels")
-                    raise ValueError(f"YOLO model expects 4-channel images, but got {src.count} channels")
-                    
-                logger.info(f"Validation successful (rasterio): {src.count} channels, {src.width}x{src.height}, dtype: {src.dtypes[0]}")
-                return True
-                
-        except Exception as e2:
-            logger.error(f"Could not validate TIFF file. Tifffile error: {str(e)}, Rasterio error: {str(e2)}")
-            raise ValueError(f"Could not validate TIFF file. Errors: tifffile={str(e)}, rasterio={str(e2)}")
-
 def predict_yolo(yolo_model, image_path, conf=0.01):
     """
     Predict using YOLO model on 4-channel TIFF image
@@ -90,9 +27,6 @@ def predict_yolo(yolo_model, image_path, conf=0.01):
     """
     logger.info(f"Starting YOLO prediction on: {image_path} with confidence: {conf}")
     
-    # Validate input file
-    validate_4channel_tiff(image_path)
-    
     logger.info("Running YOLO model inference...")
     # Run YOLO prediction directly on the input file
     results = yolo_model([image_path], conf=conf)