From e6bd5af6a8e306a1cdef63402a77a980a04ad6e1 Mon Sep 17 00:00:00 2001
From: Grafting Rayman <156515434+GraftingRayman@users.noreply.github.com>
Date: Fri, 17 Jan 2025 11:06:44 +0000
Subject: Add files via upload

---
 r_facelib/detection/__init__.py | 102 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 102 insertions(+)
 create mode 100644 r_facelib/detection/__init__.py

(limited to 'r_facelib/detection/__init__.py')

diff --git a/r_facelib/detection/__init__.py b/r_facelib/detection/__init__.py
new file mode 100644
index 0000000..3c953bd
--- /dev/null
+++ b/r_facelib/detection/__init__.py
@@ -0,0 +1,102 @@
+import os
+import torch
+from torch import nn
+from copy import deepcopy
+import pathlib
+
+from r_facelib.utils import load_file_from_url
+from r_facelib.utils import download_pretrained_models
+from r_facelib.detection.yolov5face.models.common import Conv
+
+from .retinaface.retinaface import RetinaFace
+from .yolov5face.face_detector import YoloDetector
+
+
+def init_detection_model(model_name, half=False, device='cuda'):
+    if 'retinaface' in model_name:
+        model = init_retinaface_model(model_name, half, device)
+    elif 'YOLOv5' in model_name:
+        model = init_yolov5face_model(model_name, device)
+    else:
+        raise NotImplementedError(f'{model_name} is not implemented.')
+
+    return model
+
+
+def init_retinaface_model(model_name, half=False, device='cuda'):
+    if model_name == 'retinaface_resnet50':
+        model = RetinaFace(network_name='resnet50', half=half)
+        model_url = 'https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_Resnet50_Final.pth'
+    elif model_name == 'retinaface_mobile0.25':
+        model = RetinaFace(network_name='mobile0.25', half=half)
+        model_url = 'https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_mobilenet0.25_Final.pth'
+    else:
+        raise NotImplementedError(f'{model_name} is not implemented.')
+
+    model_path = load_file_from_url(url=model_url, model_dir='../../models/facedetection', progress=True, file_name=None)
+    load_net = torch.load(model_path, map_location=lambda storage, loc: storage)
+    # remove unnecessary 'module.'
+    for k, v in deepcopy(load_net).items():
+        if k.startswith('module.'):
+            load_net[k[7:]] = v
+            load_net.pop(k)
+    model.load_state_dict(load_net, strict=True)
+    model.eval()
+    model = model.to(device)
+
+    return model
+
+
+def init_yolov5face_model(model_name, device='cuda'):
+    current_dir = str(pathlib.Path(__file__).parent.resolve())
+    if model_name == 'YOLOv5l':
+        model = YoloDetector(config_name=current_dir+'/yolov5face/models/yolov5l.yaml', device=device)
+        model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/yolov5l-face.pth'
+    elif model_name == 'YOLOv5n':
+        model = YoloDetector(config_name=current_dir+'/yolov5face/models/yolov5n.yaml', device=device)
+        model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/yolov5n-face.pth'
+    else:
+        raise NotImplementedError(f'{model_name} is not implemented.')
+    
+    model_path = load_file_from_url(url=model_url, model_dir='../../models/facedetection', progress=True, file_name=None)
+    load_net = torch.load(model_path, map_location=lambda storage, loc: storage)
+    model.detector.load_state_dict(load_net, strict=True)
+    model.detector.eval()
+    model.detector = model.detector.to(device).float()
+
+    for m in model.detector.modules():
+        if type(m) in [nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU]:
+            m.inplace = True  # pytorch 1.7.0 compatibility
+        elif isinstance(m, Conv):
+            m._non_persistent_buffers_set = set()  # pytorch 1.6.0 compatibility
+
+    return model
+
+
+# Download from Google Drive
+# def init_yolov5face_model(model_name, device='cuda'):
+#     if model_name == 'YOLOv5l':
+#         model = YoloDetector(config_name='facelib/detection/yolov5face/models/yolov5l.yaml', device=device)
+#         f_id = {'yolov5l-face.pth': '131578zMA6B2x8VQHyHfa6GEPtulMCNzV'}
+#     elif model_name == 'YOLOv5n':
+#         model = YoloDetector(config_name='facelib/detection/yolov5face/models/yolov5n.yaml', device=device)
+#         f_id = {'yolov5n-face.pth': '1fhcpFvWZqghpGXjYPIne2sw1Fy4yhw6o'}
+#     else:
+#         raise NotImplementedError(f'{model_name} is not implemented.')
+
+#     model_path = os.path.join('../../models/facedetection', list(f_id.keys())[0])
+#     if not os.path.exists(model_path):
+#         download_pretrained_models(file_ids=f_id, save_path_root='../../models/facedetection')
+
+#     load_net = torch.load(model_path, map_location=lambda storage, loc: storage)
+#     model.detector.load_state_dict(load_net, strict=True)
+#     model.detector.eval()
+#     model.detector = model.detector.to(device).float()
+
+#     for m in model.detector.modules():
+#         if type(m) in [nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU]:
+#             m.inplace = True  # pytorch 1.7.0 compatibility
+#         elif isinstance(m, Conv):
+#             m._non_persistent_buffers_set = set()  # pytorch 1.6.0 compatibility
+
+#     return model
\ No newline at end of file
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