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Raghucharan16 2025-03-01 14:34:19 +05:30
parent 058a0fa590
commit 643ac3dc35
1 changed files with 4 additions and 6 deletions
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10
deepface/models/facial_recognition/Buffalo_L.py
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@ -39,14 +39,13 @@ class Buffalo_L(FacialRecognition):
logger.info(f"Created directory: {buffalo_l_dir}") logger.info(f"Created directory: {buffalo_l_dir}")
weights_path = weight_utils.download_weights_if_necessary( weights_path = weight_utils.download_weights_if_necessary(
file_name=model_rel_path, file_name=model_rel_path,
source_url="https://drive.google.com/uc?export=download&confirm=pbef&id=1N0GL-8ehw_bz2eZQWz2b0A5XBdXdxZhg" #pylint: disable=line-too-long source_url="https://drive.google.com/uc?export=download&confirm=pbef&id=1N0GL-8ehw_bz2eZQWz2b0A5XBdXdxZhg" #pylint: disable=line-too-long
) )
if not os.path.exists(weights_path): if not os.path.exists(weights_path):
raise FileNotFoundError(f"Model file not found at: {weights_path}") raise FileNotFoundError(f"Model file not found at: {weights_path}")
else: logger.debug(f"Model file found at: {weights_path}")
logger.debug(f"Model file found at: {weights_path}")
self.model = get_model(weights_path) self.model = get_model(weights_path)
self.model.prepare(ctx_id=-1, input_size=self.input_shape) self.model.prepare(ctx_id=-1, input_size=self.input_shape)
@ -65,8 +64,7 @@ class Buffalo_L(FacialRecognition):
if len(img.shape) == 3: if len(img.shape) == 3:
img = np.expand_dims(img, axis=0) # Convert single image to batch of 1 img = np.expand_dims(img, axis=0) # Convert single image to batch of 1
elif len(img.shape) != 4: elif len(img.shape) != 4:
raise ValueError("Input must have shape (112, 112, 3) or (batch_size, 112, 112, 3).") raise ValueError(f"Input must have shape (112, 112, 3) or (X, 112, 112, 3). Got {img.shape}")
# Convert RGB to BGR for the entire batch # Convert RGB to BGR for the entire batch
img = img[:, :, :, ::-1] img = img[:, :, :, ::-1]
return img return img