Changed openmmlab addresses to huggingface ones

Author: davidpagnon

Pose2Sim/Demo_Batch/Config.toml

@@ -62,18 +62,18 @@ mode = 'balanced' # 'lightweight', 'balanced', 'performance',
 # If your pose_model is not provided in skeletons.py, you may have to create your own one (see example at the end of the file).
 # Example, equivalent to mode='balanced':
 # mode = """{'det_class':'YOLOX',
-#          'det_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.zip',
+#          'det_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.onnx',
 #          'det_input_size':[640, 640],
 #          'pose_class':'RTMPose',
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.zip',
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.onnx',
 #          'pose_input_size':[192,256]}"""
 # Example with one-stage RTMO model (Requires pose_model = 'Body'):
 # mode = """{'pose_class':'RTMO', 
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.zip', 
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.onnx', 
 #          'pose_input_size':[640, 640]}"""
 # Example with animal pose estimation:
 # mode = """{'pose_class':'RTMPose',
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.zip',
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx',
 #          'pose_input_size':[256,256]}"""
 
 

Pose2Sim/Demo_Batch/Trial_1/Config.toml

@@ -62,18 +62,18 @@
 # # If your pose_model is not provided in skeletons.py, you may have to create your own one (see example at the end of the file).
 # # Example, equivalent to mode='balanced':
 # # mode = """{'det_class':'YOLOX',
-# #          'det_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.zip',
+# #          'det_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.onnx',
 # #          'det_input_size':[640, 640],
 # #          'pose_class':'RTMPose',
-# #          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.zip',
+# #          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.onnx',
 # #          'pose_input_size':[192,256]}"""
 # # Example with one-stage RTMO model (Requires pose_model = 'Body'):
 # # mode = """{'pose_class':'RTMO', 
-# #          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.zip', 
+# #          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.onnx', 
 # #          'pose_input_size':[640, 640]}"""
 # # Example with animal pose estimation:
 # # mode = """{'pose_class':'RTMPose',
-# #          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.zip',
+# #          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx',
 # #          'pose_input_size':[256,256]}"""
 
 # det_frequency = 4 # Run person detection only every N frames, and inbetween track previously detected bounding boxes (pose estimation is still run on all frames). 

Pose2Sim/Demo_Batch/Trial_2/Config.toml

@@ -61,18 +61,18 @@ participant_mass = [70.0, 63.5]     # float (eg 70.0), or list of floats (eg [70
 # # If your pose_model is not provided in skeletons.py, you may have to create your own one (see example at the end of the file).
 # # Example, equivalent to mode='balanced':
 # # mode = """{'det_class':'YOLOX',
-# #          'det_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.zip',
+# #          'det_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.onnx',
 # #          'det_input_size':[640, 640],
 # #          'pose_class':'RTMPose',
-# #          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.zip',
+# #          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.onnx',
 # #          'pose_input_size':[192,256]}"""
 # # Example with one-stage RTMO model (Requires pose_model = 'Body'):
 # # mode = """{'pose_class':'RTMO', 
-# #          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.zip', 
+# #          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.onnx', 
 # #          'pose_input_size':[640, 640]}"""
 # # Example with animal pose estimation:
 # # mode = """{'pose_class':'RTMPose',
-# #          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.zip',
+# #          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx',
 # #          'pose_input_size':[256,256]}"""
 
 # det_frequency = 4 # Run person detection only every N frames, and inbetween track previously detected bounding boxes (pose estimation is still run on all frames). 

Pose2Sim/Demo_MultiPerson/Config.toml

@@ -62,18 +62,18 @@ mode = 'balanced' # 'lightweight', 'balanced', 'performance',
 # If your pose_model is not provided in skeletons.py, you may have to create your own one (see example at the end of the file).
 # Example, equivalent to mode='balanced':
 # mode = """{'det_class':'YOLOX',
-#          'det_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.zip',
+#          'det_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.onnx',
 #          'det_input_size':[640, 640],
 #          'pose_class':'RTMPose',
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.zip',
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.onnx',
 #          'pose_input_size':[192,256]}"""
 # Example with one-stage RTMO model (Requires pose_model = 'Body'):
 # mode = """{'pose_class':'RTMO', 
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.zip', 
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.onnx', 
 #          'pose_input_size':[640, 640]}"""
 # Example with animal pose estimation:
 # mode = """{'pose_class':'RTMPose',
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.zip',
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx',
 #          'pose_input_size':[256,256]}"""
 
 

Pose2Sim/Demo_SinglePerson/Config.toml

@@ -60,18 +60,18 @@ mode = 'balanced' # 'lightweight', 'balanced', 'performance',
 # If your pose_model is not provided in skeletons.py, you may have to create your own one (see example at the end of the file).
 # Example, equivalent to mode='balanced':
 # mode = """{'det_class':'YOLOX',
-#          'det_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.zip',
+#          'det_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.onnx',
 #          'det_input_size':[640, 640],
 #          'pose_class':'RTMPose',
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.zip',
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.onnx',
 #          'pose_input_size':[192,256]}"""
 # Example with one-stage RTMO model (Requires pose_model = 'Body'):
 # mode = """{'pose_class':'RTMO', 
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.zip', 
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.onnx', 
 #          'pose_input_size':[640, 640]}"""
 # Example with animal pose estimation:
 # mode = """{'pose_class':'RTMPose',
-#          'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.zip',
+#          'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx',
 #          'pose_input_size':[256,256]}"""
 
 

Pose2Sim/Utilities/tests.py

@@ -170,7 +170,7 @@ def test_workflow(self, mock_input):
         config_dict.get("project").update({"project_dir":project_dir})
         config_dict.get("pose").update({"pose_model":'Body'})
         config_dict.get("pose").update({"mode":"""{'pose_class':'RTMO', 
-                                                'pose_model':'https://download.openmmlab.com/mmpose/v1/projects/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.zip', 
+                                                'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.onnx', 
                                                 'pose_input_size':[640, 640]}"""})
         config_dict.get("pose").update({"display_detection":False})
         config_dict.get("pose").update({"save_video":'none'})

README.md

@@ -578,22 +578,22 @@ This will run pose estimation on your videos and save the results in the `pose`
 > ```
 > # Equivalent to mode='balanced', with body_with_feet pose model
 > mode = """{'det_class':'YOLOX',
->        'det_model':'https://download.openmmlab.com/mmpose/v1/prects/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.zip',
+>        'det_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.onnx',
 >        'det_input_size':[640, 640],
 >        'pose_class':'RTMPose',
->        'pose_model':'https://download.openmmlab.com/mmpose/v1/prects/rtmposev1/onnx_sdk/rtose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.zi,
+>        'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7-halpe26_700e-256x192-4d3e73dd_20230605.onnx',
 >        'pose_input_size':[192,256]}"""
 >
 > # With one-stage RTMO model 
 > # Requires pose_model = 'Body'. Marker augmentation won't work, Kimatic analysis will
 > mode = """{'pose_class':'RTMO', 
->        'pose_model':'https://download.openmmlab.com/mmpose/v1/prects/rtmo/onnx_sdk/rt-m_16xb16-600e_body7-640x640-39e78cc4_20231211.zip', 
+>        'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmo/onnx_sdk/rtmo-m_16xb16-600e_body7-640x640-39e78cc4_20231211.onnx', 
 >        'pose_input_size':[640, 640]}"""
 > 
 > # With animal pose estimation:
 > # Marker augmentation won't work, and you will need to create your owOpenSim skeleton for kinematic analysis.
 > mode = """{'pose_class':'RTMPose',
->        'pose_model':'https://download.openmmlab.com/mmpose/v1/prects/rtmposev1/onnx_sdk/> rtose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.zip',
+>        'pose_model':'https://huggingface.co/datasets/DavidPagnon/rtmlib_models/resolve/main/mmpose/rtmposev1/onnx_sdk/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx',
 >        'pose_input_size':[256,256]}"""
 > 
 > # Same approach for hand or face pose estimation, check the RTMLib domentation for more information.