Photorealistic filter for video game footage

Here is a step-by-step guide for creating a photorealistic filter for video game footage using the workflow and free tools mentioned:

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Step 1: Extract Video Frames

First, convert the video game footage into individual image frames.

1. Install FFmpeg:

   • Download FFmpeg from FFmpeg Official Website.
   • Add FFmpeg to your system’s PATH for easy access via the terminal/command prompt.

2. Extract Frames:

   • Open a terminal and navigate to the folder containing your video (input.mp4).
   • Run the following command:

     ffmpeg -i input.mp4 -vf fps=30 frames/frame_%04d.png
     

     • input.mp4: Replace this with your video file name.
     • fps=30: Set the output frame rate (30 frames per second).
     • frames/frame_%04d.png: Saves frames in the frames/ folder as frame_0001.png, frame_0002.png, etc.

3. Verify Output:

   • Check the frames/ folder to ensure the extracted frames are saved as images.

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Step 2: Process Frames

Option A: Apply Style Transfer with CycleGAN

1. Download CycleGAN:

   • Clone the repository:

     git clone https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix.git
     cd pytorch-CycleGAN-and-pix2pix
     

2. Install Dependencies:

   • Install required Python libraries:

     pip install -r requirements.txt
     

3. Download Pretrained Models:

   • Download a pretrained model (e.g., horse2zebra for stylistic changes or fine-tune for photorealism):

     bash ./scripts/download_cyclegan_model.sh horse2zebra
     

4. Apply Style Transfer:

   • Use the test.py script to process frames:

     python test.py --dataroot ./frames --name horse2zebra_pretrained --model test --no_dropout
     

     • Replace horse2zebra with your pretrained model.
     • Processed frames will be saved in the results/ folder.

Option B: Apply Super-Resolution with ESRGAN

1. Download ESRGAN:

   • Clone the repository:

     git clone https://github.com/xinntao/ESRGAN.git
     cd ESRGAN
     

2. Install Dependencies:

   • Install required Python libraries:

     pip install -r requirements.txt
     

3. Download Pretrained Models:

   • Download the ESRGAN model from here.

4. Run Super-Resolution:

   • Process frames using the ESRGAN script:

     python test.py --input_folder ./frames --output_folder ./processed_frames
     

     • Input: ./frames/
     • Output: ./processed_frames/

Option C: Generate Depth Maps with MiDaS

1. Download MiDaS:

   • Clone the MiDaS repository:

     git clone https://github.com/isl-org/MiDaS.git
     cd MiDaS
     

2. Install Dependencies:

   • Install PyTorch and MiDaS dependencies:

     pip install torch torchvision
     pip install -r requirements.txt
     

3. Run Depth Estimation:

   • Generate depth maps for each frame:

     python run.py --input_path ./frames --output_path ./depth_maps
     

     • Input: ./frames/
     • Output: ./depth_maps/

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Step 3: Reassemble Processed Frames into a Video

1. Ensure Processed Frames are Ordered:

   • Processed frames should be named sequentially (frame_0001.png, frame_0002.png, etc.).

2. Merge Frames into Video:

   • Run the following FFmpeg command:

     ffmpeg -framerate 30 -i processed_frames/frame_%04d.png -c:v libx264 -pix_fmt yuv420p output.mp4
     

     • -framerate 30: Match the original frame rate (30 FPS).
     • processed_frames/frame_%04d.png: Processed frames directory.
     • output.mp4: Final video file.

3. Verify Output:

   • Check the output.mp4 file to ensure it combines the processed frames into a smooth video.

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Optimizing for GTX 1650 Ti

• Resolution: Limit frame resolution to 720p (1280x720) to avoid GPU memory issues.
• Batch Processing: Process frames in batches to reduce VRAM usage.
  • Modify scripts to load and process fewer images at a time.
• Mixed Precision: Use PyTorch's torch.cuda.amp for mixed-precision training or inference to save VRAM.

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Potential Enhancements

1. Dataset Fine-Tuning:

   • Train CycleGAN or ESRGAN on a custom dataset with real-world images for better photorealism.
   • Use datasets like COCO or Flickr for training.

2. Post-Processing:

   • Add cinematic effects using DaVinci Resolve (free) for professional video editing.

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Let me know if you’d like help setting up any of these tools or troubleshooting specific issues!