no torch dependency if running on CPU

.gitignore

@@ -1,4 +1,5 @@
 **/__pycache__/
+**/build/
 *.pyc
 logs.txt*
 **/*.log

Pose2Sim/Utilities/reproj_from_trc_calib.py

@@ -408,4 +408,4 @@ if __name__ == '__main__':
     parser.add_argument('-O', '--output_file_root', required=False, help='output file root path, without extension')
     args = vars(parser.parse_args())
 
-    reproj_from_trc_calib_func(**args)
+    reproj_from_trc_calib_func(**args) 

Pose2Sim/poseEstimation.py

@@ -39,7 +39,6 @@ import logging
 from tqdm import tqdm
 import numpy as np
 import cv2
-import torch
 import onnxruntime as ort
 
 from rtmlib import PoseTracker, Body, Wholebody, BodyWithFeet, draw_skeleton
@@ -359,10 +358,15 @@ def rtm_estimator(config_dict):
             frame_rate = 60    
 
     # If CUDA is available, use it with ONNXRuntime backend; else use CPU with openvino
-    if 'CUDAExecutionProvider' in ort.get_available_providers() and torch.cuda.is_available():
-        device = 'cuda'
-        backend = 'onnxruntime'
-        logging.info(f"\nValid CUDA installation found: using ONNXRuntime backend with GPU.")
+    if 'CUDAExecutionProvider' in ort.get_available_providers():
+        try:
+            import torch
+            if torch.cuda.is_available() == False:
+                device = 'cuda'
+                backend = 'onnxruntime'
+                logging.info(f"\nValid CUDA installation found: using ONNXRuntime backend with GPU.")
+        except:
+            pass
     elif 'MPSExecutionProvider' in ort.get_available_providers() or 'CoreMLExecutionProvider' in ort.get_available_providers():
         device = 'mps'
         backend = 'onnxruntime'

setup.cfg

@@ -36,7 +36,7 @@ install_requires =
     lxml==4.9.4
     matplotlib
     mpl_interactions
-    Pillow
+    # Pillow
     PyQt5
     tqdm
     anytree
@@ -47,7 +47,7 @@ install_requires =
     ipython
     c3d
     tensorflow
-    torch
+    # torch
     rtmlib
     onnxruntime
     openvino