def save_batch_image_with_joints()

in lib/utils/vis.py [0:0]

• 30 lines of code
• 6 McCabe index (conditional complexity)

def save_batch_image_with_joints(batch_image, batch_joints, batch_joints_vis,
                                 file_name, nrow=8, padding=2):
    '''
    batch_image: [batch_size, channel, height, width]
    batch_joints: [batch_size, num_joints, 3],
    batch_joints_vis: [batch_size, num_joints, 1],
    }
    '''
    grid = torchvision.utils.make_grid(batch_image, nrow, padding, True)
    ndarr = grid.mul(255).clamp(0, 255).byte().permute(1, 2, 0).cpu().numpy()
    ndarr = ndarr.copy()

    nmaps = batch_image.size(0)
    xmaps = min(nrow, nmaps)
    ymaps = int(math.ceil(float(nmaps) / xmaps))
    height = int(batch_image.size(2) + padding)
    width = int(batch_image.size(3) + padding)
    k = 0
    for y in range(ymaps):
        for x in range(xmaps):
            if k >= nmaps:
                break
            joints = batch_joints[k]
            joints_vis = batch_joints_vis[k]

            for joint, joint_vis in zip(joints, joints_vis):
                joint[0] = x * width + padding + joint[0]
                joint[1] = y * height + padding + joint[1]
                if joint_vis[0]:
                    cv2.circle(ndarr, (int(joint[0]), int(joint[1])), 2, [255, 0, 0], 2)
            k = k + 1
    cv2.imwrite(file_name, ndarr)