• sales

    +86-0755-88291180

Converting MP4 video into gif User Guide

【Mp4 to gif steps】

1.Prepare mp4 files and python scripts provided by us:


2.Open python file and check the modified source code:


3.Find the code that defines the video path and modify the path to your own video path:


4.Find the time interval code that defines the interception of mp4 frames, and modify the time interval customized for your video (as shown below, the interception start time is 1 second and the interception end time is 60 seconds):


5.Find the code that defines the size of gif, and customize the value of the modified size (the value on the left is width and the value on the right is height):


6.Find the code that defines the storage path of gif files, and modify it to your customized path and name:


7.After configuring your own parameters, click Run python file and wait for a while to generate a gif file (Note: when the file duration is too long or the gif generation is too large, the program will crash, so the time interval and picture size should be set reasonably):

python3 mp4_to_gif.py

8.Python file running effect:


【Code】

import cv2

import io

from PIL import Image, ImageOps

# Open the video file

cap = cv2.VideoCapture('./bad_apple.mp4')


# Get the total frame number and frame rate.

frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))

fps = cap.get(cv2.CAP_PROP_FPS)


# Defines the time interval (in seconds) to be intercepted.

start_time = 1

end_time = 60


# Calculate the corresponding frame number interval

start_frame = int(start_time * fps)

end_frame = int(end_time * fps)


# Move to the start frame

cap.set(cv2.CAP_PROP_POS_FRAMES, start_frame)

# Declare a memory buffer

buffer = bytearray()

images = []

# Traverse every frame in the frame number interval from the start frame.

for i in range(start_frame, end_frame):

    # Read the next frame

    ret, frame = cap.read()


    # If the frame reading fails, exit the loop.

    if not ret:

        break


    # Encode the frame into JPEG image data and store it in the memory buffer.

    _, enc_frame = cv2.imencode(".jpg", frame)

    buffer.extend(enc_frame)

    images.append(Image.open(io.BytesIO(buffer)))


    # Empty the buffer

    buffer = bytearray()


# Release the video file handle.

cap.release()

cv2.destroyAllWindows()


# Transform the picture and save it as a GIF file.

new_frames = []

for frame in images:

    frame = ImageOps.fit(frame, (256, 128), method=Image.ANTIALIAS)

    new_frames.append(frame)

new_frames[0].save('movie_new.gif', save_all=True, append_images=new_frames[1:], duration=5, loop=0)


【The effect of generating GIF files】


TAG: ESP32-S3 A7670E 4G development board supports LTE Cat-1/2G/GNSS positioning/WiFi/Bluetooth Raspberry Pi MIPI Raspberry Pi AI Camera Official Original 12MP IMX500 Intelligent visual Sensor On-Board RP2040 Rockchip Raspberry Pi 6.25 inch DSI Display MIPI LCD Capacitive TouchScreen 720x1560 RV1103 USB Camera 2MP GC2093 ‌WDR Backlight Compensation‌ Onboard microphone RS232 to CAN Raspberry Pi 60GHz mmWave Radar Sensor High-Precision Human Body PCR For Arduino ESP32 AURORA AI Laser Radar And Dual Eye Camera IMU Integrated Positioning Map For Android/ROS+RoboStudio Core3566102032 Industrial Isolated RS485 TO ETH (C) RJ45 Converter Wall/Rail-Mount For Modbus Raspberry Pi Camera Gripper Serial Robotic Arm Gripper Mechanical claw Serial Bus Servo ST3215/CF35-12 ESP32-C6 Development Board Computer AI Deepseek Mechanical Voice Keyboard Linux 10x0.85inch LCD Screen Customize keys + 2.01 inch Secondary Display DeepSeek AI Voice Chat ESP32 C6 Development Board 2.06-inch AMOLED Display 410×502 2.06inch TouchScreen Programmable Watch Raspberry Pi display ESP32 S3 AI 0.85inch mini tiny Development Board 0.85 inch DeepSeek RGB LED UART Serial TTL To RS232 B Built-In Protection Circuits Rail-mount