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raghucharan16 2025-02-28 15:11:59 +05:30
parent 0d7c36a63b
commit 1a5d74b893
1 changed files with 17 additions and 15 deletions
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32
deepface/models/facial_recognition/Buffalo_L.py
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@ -2,14 +2,6 @@ import os
import numpy as np import numpy as np
from typing import List from typing import List
try:
from insightface.model_zoo import get_model
except ModuleNotFoundError as err:
raise ModuleNotFoundError(
"InsightFace is an optional dependency for the Buffalo_L model."
"You can install it with: pip install insightface>=0.7.3"
) from err
from deepface.commons import weight_utils, folder_utils from deepface.commons import weight_utils, folder_utils
from deepface.commons.logger import Logger from deepface.commons.logger import Logger
from deepface.models.FacialRecognition import FacialRecognition from deepface.models.FacialRecognition import FacialRecognition
@ -27,20 +19,30 @@ class Buffalo_L(FacialRecognition):
""" """
Load the InsightFace Buffalo_L recognition model. Load the InsightFace Buffalo_L recognition model.
""" """
# Define the relative model path try:
model_rel_path = os.path.join("buffalo_l", "w600k_r50.onnx") from insightface.model_zoo import get_model
except ModuleNotFoundError as err:
raise ModuleNotFoundError(
"InsightFace is an optional dependency for the Buffalo_L model."
"You can install it with: pip install insightface>=0.7.3"
) from err
# Get the DeepFace weights directory # Define the model filename and subdirectory
sub_dir = "buffalo_l"
model_file = "w600k_r50.onnx"
model_rel_path = os.path.join(sub_dir, model_file)
# Get the DeepFace home directory and construct weights path
home = folder_utils.get_deepface_home() home = folder_utils.get_deepface_home()
weights_dir = os.path.join(home, ".deepface", "weights") weights_dir = os.path.join(home, ".deepface", "weights")
buffalo_l_dir = os.path.join(weights_dir, "buffalo_l") buffalo_l_dir = os.path.join(weights_dir, sub_dir)
# Ensure the buffalo_l subdirectory exists # Ensure the buffalo_l subdirectory exists
if not os.path.exists(buffalo_l_dir): if not os.path.exists(buffalo_l_dir):
os.makedirs(buffalo_l_dir, exist_ok=True) os.makedirs(buffalo_l_dir, exist_ok=True)
logger.info(f"Created directory: {buffalo_l_dir}") logger.info(f"Created directory: {buffalo_l_dir}")
# Download the model weights # Download the model weights if not already present
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" source_url="https://drive.google.com/uc?export=download&confirm=pbef&id=1N0GL-8ehw_bz2eZQWz2b0A5XBdXdxZhg"
@ -52,8 +54,8 @@ class Buffalo_L(FacialRecognition):
else: else:
raise FileNotFoundError(f"Model file not found at: {weights_path}") raise FileNotFoundError(f"Model file not found at: {weights_path}")
# Load the model using the full absolute path # Load the model
self.model = get_model(weights_path) self.model = get_model(model_file, root=buffalo_l_dir)
self.model.prepare(ctx_id=-1, input_size=self.input_shape) self.model.prepare(ctx_id=-1, input_size=self.input_shape)
def preprocess(self, img: np.ndarray) -> np.ndarray: def preprocess(self, img: np.ndarray) -> np.ndarray: