def fetch()

in run.py [0:0]

• 46 lines of code
• 22 McCabe index (conditional complexity)

def fetch(subjects, action_filter=None, subset=1, parse_3d_poses=True):
    out_poses_3d = []
    out_poses_2d = []
    out_camera_params = []
    for subject in subjects:
        for action in keypoints[subject].keys():
            if action_filter is not None:
                found = False
                for a in action_filter:
                    if action.startswith(a):
                        found = True
                        break
                if not found:
                    continue
                
            poses_2d = keypoints[subject][action]
            for i in range(len(poses_2d)): # Iterate across cameras
                out_poses_2d.append(poses_2d[i])
                
            if subject in dataset.cameras():
                cams = dataset.cameras()[subject]
                assert len(cams) == len(poses_2d), 'Camera count mismatch'
                for cam in cams:
                    if 'intrinsic' in cam:
                        out_camera_params.append(cam['intrinsic'])
                
            if parse_3d_poses and 'positions_3d' in dataset[subject][action]:
                poses_3d = dataset[subject][action]['positions_3d']
                assert len(poses_3d) == len(poses_2d), 'Camera count mismatch'
                for i in range(len(poses_3d)): # Iterate across cameras
                    out_poses_3d.append(poses_3d[i])
    
    if len(out_camera_params) == 0:
        out_camera_params = None
    if len(out_poses_3d) == 0:
        out_poses_3d = None
    
    stride = args.downsample
    if subset < 1:
        for i in range(len(out_poses_2d)):
            n_frames = int(round(len(out_poses_2d[i])//stride * subset)*stride)
            start = deterministic_random(0, len(out_poses_2d[i]) - n_frames + 1, str(len(out_poses_2d[i])))
            out_poses_2d[i] = out_poses_2d[i][start:start+n_frames:stride]
            if out_poses_3d is not None:
                out_poses_3d[i] = out_poses_3d[i][start:start+n_frames:stride]
    elif stride > 1:
        # Downsample as requested
        for i in range(len(out_poses_2d)):
            out_poses_2d[i] = out_poses_2d[i][::stride]
            if out_poses_3d is not None:
                out_poses_3d[i] = out_poses_3d[i][::stride]
    

    return out_camera_params, out_poses_3d, out_poses_2d