Sweep: use DeepFace

[a0ali0taha]

Using DeepFace library check video frames if it contains women face blure it

Checklist

- [X] `all.py` > • At the top of the file, add the following import statement to import the DeepFace library: `from deepface import DeepFace` > • After the `detach_audio` function, define a new function `blur_female_faces` that takes a video path as input and returns a new video with female faces blurred. This function should: > - Load the video and iterate over its frames > - For each frame, use DeepFace to detect faces and their genders > - If a face is identified as female, apply a blur effect to the region of the frame containing the face > - Combine the processed frames into a new video and return its path > • In the main part of the script, after the `download_youtube_video` function is called and before the `detach_audio` function is called, call the `blur_female_faces` function on the downloaded video.

[sweep-ai[bot]]

Here's the PR! https://github.com/a0ali0taha/cleanvedio/pull/9.

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Step 1: 🔍 Code Search

I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.

Some code snippets I looked at (click to expand). If some file is missing from here, you can mention the path in the ticket description.

https://github.com/a0ali0taha/cleanvedio/blob/6b92cf46c1a6f1860020f3935e0d55dc5d06167d/all.py#L1-L126 https://github.com/a0ali0taha/cleanvedio/blob/6b92cf46c1a6f1860020f3935e0d55dc5d06167d/spleeter.py#L1-L39 https://github.com/a0ali0taha/cleanvedio/blob/6b92cf46c1a6f1860020f3935e0d55dc5d06167d/download.py#L1-L18 https://github.com/a0ali0taha/cleanvedio/blob/6b92cf46c1a6f1860020f3935e0d55dc5d06167d/spleeter_code.py#L1-L4 https://github.com/a0ali0taha/cleanvedio/blob/6b92cf46c1a6f1860020f3935e0d55dc5d06167d/detach.py#L1-L38

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Step 2: 🧐 Snippet Analysis

From looking through the relevant snippets, I decided to make the following modifications:

File Path

Proposed Changes

all.py

Modify all.py with contents: • At the top of the file, add the following import statement to import the DeepFace library: from deepface import DeepFace • After the detach_audio function, define a new function blur_female_faces that takes a video path as input and returns a new video with female faces blurred. This function should: - Load the video and iterate over its frames - For each frame, use DeepFace to detect faces and their genders - If a face is identified as female, apply a blur effect to the region of the frame containing the face - Combine the processed frames into a new video and return its path • In the main part of the script, after the download_youtube_video function is called and before the detach_audio function is called, call the blur_female_faces function on the downloaded video.

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Step 3: 📝 Planning

I have created a plan for writing the pull request. I am now working my plan and coding the required changes to address this issue. Here is the planned pull request:

Add face detection and blurring using DeepFace library sweep/deepface-face-detection

Description

This PR adds the functionality to detect faces in video frames using the DeepFace library and blur them if they are identified as female. The DeepFace library is a deep learning facial recognition system that provides accurate face detection and gender classification.

Summary

• Added import statement for the DeepFace library at the top of the all.py file.
• Implemented a new function blur_female_faces that takes a video path as input and returns a new video with female faces blurred. This function uses DeepFace to detect faces and their genders, applies a blur effect to female faces, and combines the processed frames into a new video.
• Integrated the blur_female_faces function into the existing video processing pipeline, ensuring that it is applied after the video is downloaded and before the audio is detached.
• Updated the main script to call the blur_female_faces function on the downloaded video.
• Added necessary dependencies and ensured compatibility with the DeepFace library.

This PR enhances the functionality of the codebase by adding face detection and blurring, improving the privacy and anonymity of individuals in the processed videos.

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Step 4: ⌨️ Coding

File	Instructions	Progress
all.py	Modify all.py with contents: • At the top of the file, add the following import statement to import the DeepFace library: from deepface import DeepFace • After the detach_audio function, define a new function blur_female_faces that takes a video path as input and returns a new video with female faces blurred. This function should: - Load the video and iterate over its frames - For each frame, use DeepFace to detect faces and their genders - If a face is identified as female, apply a blur effect to the region of the frame containing the face - Combine the processed frames into a new video and return its path • In the main part of the script, after the download_youtube_video function is called and before the detach_audio function is called, call the blur_female_faces function on the downloaded video.	✅ Commit c8720a1	I have finished coding the issue. I am now reviewing it for completeness.

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Step 5: 🔁 Code Review

Here are my self-reviews of my changes at sweep/deepface-face-detection.

Here is the 1st review

Thanks for your contribution. There are a few changes that need to be made:

• In all.py on lines 33-66, you've used a function blur_face which is not defined or imported anywhere in the code. Please define this function or import it from a library.
• Also in all.py on lines 33-66, you've used the DeepFace.analyze function on the frame data from the video. Please ensure that the frame data is in a format that this function can handle.

Once these changes are made, we can proceed with merging this pull request.

I finished incorporating these changes.

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