How to Play a Video in Slow Motion Using OpenCV in Python

Introduction

Have you ever wanted to play a video in slow motion using Python? Whether you are analyzing motion, working on video processing projects, or just experimenting with OpenCV, playing a video in slow motion can be useful.

In this blog, we will walk through how to play a video in slow motion using OpenCV, explain how frame rates work, and provide a step-by-step Python script to achieve smooth slow-motion playback.

Understanding Frame Rate and Slow Motion

Videos are essentially a sequence of images (frames) displayed rapidly to create motion. The frame rate (FPS – Frames Per Second) determines how many frames are shown per second.

For example:

30 FPS means 30 frames are displayed per second (standard for most videos).
60 FPS means 60 frames per second (smoother motion).

To play a video in slow motion, we need to reduce the playback speed by increasing the delay between frames.

For example:

A 30 FPS video played at half speed should display each frame for twice as long.
A 60 FPS video played at one-quarter speed should display each frame for four times as long.

Installing OpenCV

Before we start coding, ensure you have OpenCV installed. If not, install it using:

pip install opencv-python

Playing a Video in Slow Motion Using OpenCV

Step 1: Load the Video File

We use cv2.VideoCapture() to open the video file.

Step 2: Read Frames from the Video

We use a loop to read frames one by one.

Step 3: Adjust the Delay for Slow Motion

We introduce a delay using cv2.waitKey() to slow down playback.

import cv2  

# Load the video file
video_path = "video.mp4"  # Replace with your video file path
cap = cv2.VideoCapture(video_path)  

# Get the original FPS of the video
fps = int(cap.get(cv2.CAP_PROP_FPS))
print(f"Original FPS: {fps}")

# Set slow-motion factor (2x slower)
slow_factor = 2  
delay = int(1000 / fps) * slow_factor  # Increase delay for slow motion

while cap.isOpened():
    ret, frame = cap.read()  # Read a frame

    if not ret:
        break  # If no more frames, exit loop

    cv2.imshow("Slow Motion Video", frame)  # Show frame

    if cv2.waitKey(delay) & 0xFF == ord('q'):  # Press 'q' to exit
        break  

cap.release()  # Release the video
cv2.destroyAllWindows()  # Close all OpenCV windows

How Does This Code Work?

1️⃣ Load the Video

cap = cv2.VideoCapture(“video.mp4”)

This opens the video file for reading.

2️⃣ Get the Video’s FPS

fps = int(cap.get(cv2.CAP_PROP_FPS))

This extracts the frames per second (FPS) of the video.

3️⃣ Adjust Playback Speed

slow_factor = 2
delay = int(1000 / fps) * slow_factor

We increase the delay between frames to slow down playback.
1000 / fps gives the frame delay in milliseconds.
Multiplying by slow_factor slows the video down.

4️⃣ Play Video Frame-by-Frame

while cap.isOpened():
ret, frame = cap.read()

This reads and displays each frame.
If there are no more frames, the loop exits.

5️⃣ Show Frames with Slow Motion

cv2.imshow(“Slow Motion Video”, frame)
cv2.waitKey(delay)

Each frame is displayed for a longer duration, creating the slow-motion effect.
Press ‘q’ to exit playback.

Customizing the Slow Motion Effect

1️⃣ Make the Video Slower or Faster

Change the slow_factor:

slow_factor = 3 # 3x slower

A higher value slows the video more.

2️⃣ Play Only a Specific Portion of the Video

Modify the loop to start and stop at specific timestamps:

start_time = 5  # Start from 5 seconds
end_time = 15  # Stop at 15 seconds

cap.set(cv2.CAP_PROP_POS_MSEC, start_time * 1000)  # Set start position

while cap.isOpened():
    current_time = cap.get(cv2.CAP_PROP_POS_MSEC) / 1000  # Convert to seconds
    if current_time > end_time:
        break  # Stop at end_time

This will play only the portion between 5 and 15 seconds in slow motion.

Handling Common Errors

1️⃣ “Could not open video file”

If OpenCV fails to open your video file, check the path:

if not cap.isOpened():
print(“Error: Could not open video file.”)

Make sure the file exists and is in the correct format (MP4, AVI, etc.).

2️⃣ “Video is lagging too much”

If the video lags, try a lower slow_factor or use a smaller video resolution:

frame = cv2.resize(frame, (640, 480))

This reduces the frame size for smoother playback.

Final Thoughts

Playing a video in slow motion using OpenCV is simple and highly customizable. You can:
✔ Adjust slow-motion speed using slow_factor.
✔ Play only a specific portion of the video.
✔ Resize frames to optimize performance.

This technique can be used for sports analysis, motion detection, or just for fun! 🎥

🚀 Try it out with your own videos and experiment with different speeds!