How to Automate 10,000 Video‑Channel Posts with Python and OCR for Massive Traffic

Abstract: Using simple Python techniques, you can generate 10,000 deduplicated videos for WeChat Video Channels to capture traffic. By posting 100 exposures per video, 10,000 videos yield one million exposures, using quantity to win over the platform’s recommendation algorithm.

Video‑channel commerce works like other short‑video platforms: you post a video, promote a product, and earn commissions when users purchase through your link.

Where is the traffic?

Key observations from industry discussions:

Content that went viral on other platforms will likely re‑viral on Video Channels.

Massive quantity can counteract the uncertainty of the platform’s recommendation algorithm.

Short‑video platforms deduplicate video content but not audio.

Therefore, batch‑generating videos that bypass video deduplication while reusing audio is an effective strategy.

Data acquisition

Search for high‑quality chat screenshots using keywords like "funny conversation". These images often contain real chat data, making them both entertaining and valuable.

Use a Python web‑scraper to download the images. Basic Python knowledge is sufficient.

The following code (provided at the end of the article) fetches images from Baidu:

OCR processing

Extract text from the downloaded chat screenshots using the custom imgocr project, which includes a built‑in OCR model.

After running the OCR, you obtain clean textual chat data ready for video generation.

Generating chat videos

Chat videos consist of a sequence of images that simulate a conversation. First, locate a web tool that generates WeChat‑style chat screenshots (search "WeChat chat image generator"). Automate the tool with a headless browser to capture the generated images.

Save the tool locally (e.g., using the "Save All Resources" browser extension) and run it on your machine:

Generate a batch of chat images, then stitch them into a silent video using any video‑editing library.

Acquiring audio

Since platforms do not deduplicate audio, you can download audio tracks from similar videos on short‑video platforms (e.g., Douyin) and reuse them.

Extract audio from downloaded videos with moviepy:

from moviepy.editor import AudioFileClip
my_audio_clip = AudioFileClip("my_video.mp4")
my_audio_clip.write_audiofile("my_audio.wav")

Assembling the final video

Combine the silent chat video with a randomly selected audio track to produce a complete video.

The resulting video includes both visual chat content and audio, ready for upload to the Video Channel.

Conclusion

Video Channels are currently booming, offering significant earning opportunities.

By applying the three earlier conclusions, you can use scripts to mass‑produce videos and monetize the traffic.

The tutorial demonstrates a technically complex example (funny chat videos) that can be adapted to other content types.

A step‑by‑step workflow—from data collection to final video assembly—is provided.

All code referenced in the article is shared at the end; feel free to reach out for assistance.