Camshowrecordings/model/sam_samantha/5 〈RECENT〉

model: name: sam_samantha version: 5 backbone: vit_h image_size: 1024 num_classes: 1 # Usually segmentation → binary mask preprocess: normalize: true mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] device: cuda Below is a minimal, self‑contained script that loads the model and runs a single inference on a video frame.

In short: camshowrecordings/model/sam_samantha/5 points to the of the SAM‑Samantha model inside the CamShowRecordings codebase. 2️⃣ Prerequisites | Requirement | Why You Need It | Quick Install | |-------------|----------------|---------------| | Python ≥ 3.8 | Most model code (PyTorch / TensorFlow) runs on modern Python. | python -V sudo apt-get install python3 (Linux) | | Git | To clone the repo or pull updates. | git --version | | Virtual Environment (venv, conda, poetry) | Keeps dependencies isolated. | python -m venv venv && source venv/bin/activate | | PyTorch ≥ 2.0 (or TensorFlow if the repo uses TF) | Underlying deep‑learning framework. | pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 | | OpenCV | For loading video frames and visualising results. | pip install opencv-python | | NumPy, tqdm | Common utilities. | pip install numpy tqdm | | Optional: CUDA Toolkit | If you want GPU acceleration. | Follow NVIDIA’s installer for your GPU. | Tip: Most projects ship a requirements.txt or environment.yml . After cloning the repo, just run pip install -r requirements.txt (or conda env create -f environment.yml ). 3️⃣ Repository Layout (Typical) camshowrecordings/ │ ├─ data/ # Raw video recordings, annotation files, etc. │ ├─ model/ │ └─ sam_samantha/ │ ├─ 5/ │ │ ├─ config.yaml # Model hyper‑parameters & architecture │ │ ├─ model.ckpt # Serialized weights (PyTorch checkpoint) │ │ ├─ tokenizer/ # If the model uses any tokenizers │ │ └─ README.md # Model‑specific notes │ ├─ 4/ ... (older versions) │ └─ latest -> 5/ # Symlink to the newest version │ ├─ scripts/ # Example utilities, e.g., run_inference.py │ ├─ notebooks/ # Jupyter notebooks for exploration │ └─ README.md If you only see latest pointing to 5 , you’re already looking at the most recent release. 4️⃣ Getting the Code # 1️⃣ Clone the repo (replace URL with the actual one) git clone https://github.com/yourorg/camshowrecordings.git cd camshowrecordings camshowrecordings/model/sam_samantha/5

cd model/sam_samantha/5 ls -l Typical files you’ll see: | python -V sudo apt-get install python3 (Linux)

frame_idx = 0 while True: ret, frame = cap.read() if not ret: break 0.406] std: [0.229

Open config.yaml to verify things like:

if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("input_video", type=Path) parser.add_argument("output_video", type=Path) parser.add_argument("--stride", type=int, default=5, help="Run inference every N frames (default=5)") args = parser.parse_args() process_video(args.input_video, args.output_video, args.stride)

parser = argparse.ArgumentParser(description="Run SAM‑Samantha v5 on a frame") parser.add_argument("image_path", type=str, help="Path to an image (or a video frame)") args = parser.parse_args()