I wanted to stack vertically 5 videos with cv2.VideoWriter, however something is off with the dimensions, as in the attached image. Each data is of size (400, 100) for (x, y).

frame from the wrongly stacked video

Here is the code:

# Set up video writer
fps = 30
size = (400, 100*5)  # Dimensions for lbs2d
video2 = cv2.VideoWriter('flow_data_video_new.mp4', cv2.VideoWriter_fourcc(*'mp4v'), fps, size)

# Load flow data
flow_gt = load_data('flow_gt.pkl')
flow_pred_1 = load_data('flow_pred_1.pkl')
flow_diff_1 = load_data('flow_diff_1.pkl')
flow_pred_2 = load_data('flow_pred_2.pkl')
flow_diff_2 = load_data('flow_diff_2.pkl')

# just to make it faster
flow_gt = flow_gt[:10]
flow_pred_1 = flow_pred_1[:10]
flow_diff_1 = flow_diff_1[:10]
flow_pred_2 = flow_pred_2[:10]
flow_diff_2 = flow_diff_2[:10]

# Determine the length of the shortest data array
min_length = min(len(flow_gt), len(flow_pred_1), len(flow_diff_1), len(flow_pred_2), len(flow_diff_2))

# Flow Data Visualization
quiver_steps = 6
max_flow_gt = np.max([np.max(np.sqrt(u**2 + v**2)) for field in [flow_gt, flow_pred_1, flow_diff_1, flow_pred_2, flow_diff_2] for u, v in zip(field[:, 0, ...], field[:, 1, ...])])

# Create video frames
for i in range(min_length):
    # Create a blank image for the video frame
    frame = np.zeros((500, 400, 3), dtype=np.uint8)  # 400x500 for 5 stacked images
    
    # List of flow fields to process
    fields = [flow_gt, flow_pred_1, flow_diff_1, flow_pred_2, flow_diff_2]
    
    for j, field in enumerate(fields):
        u = field[i, 0, ...]
        v = field[i, 1, ...]
        norm = np.sqrt(u ** 2 + v ** 2)
        img = np.zeros(u.shape)
        
        # Create the quiver plot and save it as an image
        fig, ax = plt.subplots(figsize=(5, 1), dpi=100)
        pyimof.display.quiver(u, v, c=norm, bg=img, ax=ax, cmap='turbo', clim=(0, max_flow_gt), scale=None, bg_cmap='gray', step=quiver_steps)
        ax.axis('off')
        plt.subplots_adjust(left=0, right=1, top=1, bottom=0)
        
        # Convert the Matplotlib figure to an image
        fig.canvas.draw()
        image = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
        image = image.reshape(500, 400, 3)
        
        # Insert the image into the frame
        frame[j*100:(j+1)*100, :, :] = cv2.resize(image, (400, 100))
        
        plt.close(fig)
        print("x")
    
    # Write the frame to the video
    video2.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))

video2.release()
    

I tried to debug it but something is still off, any help will be appreciated!