import torch
#from mmaction.apis import init_recognizer, inference_recognizer
print(torch.__version__)
print(torch.cuda.is_available())
#config_file = 'configs/recognition/tsn/tsn_r50_video_inference_1x1x3_100e_kinetics400_rgb.py'
#device = 'cuda:0' # 或 'cpu'
#device = torch.device(device)

#model = init_recognizer(config_file, device=device)
# 进行演示视频的推理
#inference_recognizer(model, 'demo/demo.mp4', 'demo/label_map_k400.txt')
import torch
#from mmaction.apis import init_recognizer, inference_recognizer
print(torch.__version__)
print(torch.cuda.is_available())
#config_file = 'configs/recognition/tsn/tsn_r50_video_inference_1x1x3_100e_kinetics400_rgb.py'
#device = 'cuda:0' # 或 'cpu'
#device = torch.device(device)

#model = init_recognizer(config_file, device=device)
# 进行演示视频的推理
#inference_recognizer(model, 'demo/demo.mp4', 'demo/label_map_k400.txt')
#from mmaction.apis import init_recognizer, inference_recognizer #config_file = 'configs/recognition/tsn/tsn_r50_video_inference_1x1x3_100e_kinetics400_rgb.py' #device = 'cuda:0' # 或 'cpu' #device = torch.device(device) #model = init_recognizer(config_file, device=device) # 进行演示视频的推理 #inference_recognizer(model, 'demo/demo.mp4', 'demo/label_map_k400.txt')