def nms(dets, thresh, force_cpu=False): """Dispatch to either CPU or GPU NMS implementations.""" if dets.shape[0] == 0: return [] # ---numpy version--- # original: return gpu_nms(dets, thresh, device_id=cfg.GPU_ID) # ---pytorch version--- return nms_gpu(dets, thresh)
def nms(dets, thresh, force_cpu=False): """Dispatch to either CPU or GPU NMS implementations.""" if dets.shape[0] == 0: return [] if cfg.USE_GPU_NMS and not force_cpu: # ---numpy version--- # original: return gpu_nms(dets, thresh, device_id=cfg.GPU_ID) # ---pytorch version--- return nms_gpu(dets, thresh) else: keep = cpu_nms(dets.numpy(), thresh) return torch.Tensor(keep)
def nms(dets, thresh, force_cpu=False): """Dispatch to either CPU or GPU NMS implementations.""" if dets.shape[0] == 0: print("dets shape is 0...!!!!!!!!!!!!!!!!!!!!!!!") return [] # ---numpy version--- # original: return gpu_nms(dets, thresh, device_id=cfg.GPU_ID) # ---pytorch version--- if not force_cpu: return nms_gpu(dets, thresh) else: dets = dets.numpy() keep=cpu_nms(dets, thresh) return torch.from_numpy(np.array(keep)).float().to("cuda:1") #converting to float tensor tensor
def nms(dets, thresh, force_cpu=False): """Dispatch to either CPU or GPU NMS implementations.""" if dets.shape[0] == 0: return [] # ---numpy version--- # original: return gpu_nms(dets, thresh, device_id=cfg.GPU_ID) # ---pytorch version--- # Force nms_gpu Compile check try: return nms_gpu(dets, thresh) if force_cpu == False else nms_cpu( dets, thresh) except NameError: return nms_cpu(dets, thresh)