Added new correct cropping for training and smoothing for video.

natanielruiz

2017-08-08 18a21d4b07c581a8954b08518115fb035c712b28

 code/test_on_video.py

@@ -45,10 +45,12 @@
    if not os.path.exists(args.video_path):
        sys.exit('Video does not exist')

    # ResNet50 with 3 outputs.
    model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
    # ResNet101 with 3 outputs.
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 23, 3], 66)
    # ResNet50
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
    # ResNet18
    # model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66)
    model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66)

    print 'Loading snapshot.'
    # Load snapshot
@@ -79,6 +81,8 @@
    fourcc = cv2.VideoWriter_fourcc(*'MJPG')
    out = cv2.VideoWriter('output/video/output-%s.avi' % args.output_string, fourcc, 30.0, (width, height))

    txt_out = open('output/video/output-%s.txt' % args.output_string, 'w')

    bbox_file = open(args.bboxes, 'r')
    frame_num = 1

@@ -95,6 +99,7 @@
            out.release()
            video.release()
            bbox_file.close()
            txt_out.close()
            sys.exit(0)

        # Save all frames as they are if they don't have bbox annotation.
@@ -104,6 +109,7 @@
                out.release()
                video.release()
                bbox_file.close()
                txt_out.close()
                sys.exit(0)
            out.write(frame)
            frame_num += 1
@@ -113,6 +119,7 @@
            out.release()
            video.release()
            bbox_file.close()
            txt_out.close()
            sys.exit(0)

        x_min, y_min, x_max, y_max = int(line[1]), int(line[2]), int(line[3]), int(line[4])
@@ -136,6 +143,7 @@
        roll_predicted = torch.sum(roll_predicted.data[0] * idx_tensor) * 3 - 99

        # Print new frame with cube and TODO: axis
        txt_out.write(str(frame_num) + ' %f %f %f\n' % (yaw_predicted, pitch_predicted, roll_predicted))
        utils.plot_pose_cube(frame, yaw_predicted, pitch_predicted, roll_predicted, (x_min + x_max) / 2, (y_min + y_max) / 2, size = 200)
        out.write(frame)

@@ -147,6 +155,7 @@
            out.release()
            video.release()
            bbox_file.close()
            txt_out.close()
            sys.exit(0)
        out.write(frame)
        frame_num += 1