diff --git a/README.md b/README.md index 669242df..e9015750 100644 --- a/README.md +++ b/README.md @@ -59,49 +59,42 @@ This breakthrough is driven by an innovative data engine that has automatically ### Prerequisites +- [uv](https://github.com/astral-sh/uv) installed - Python 3.12 or higher -- PyTorch 2.7 or higher - CUDA-compatible GPU with CUDA 12.6 or higher -1. **Create a new Conda environment:** +1. **Clone the repository:** ```bash -conda create -n sam3 python=3.12 -conda deactivate -conda activate sam3 +git clone https://github.com/facebookresearch/sam3.git +cd sam3 ``` -2. **Install PyTorch with CUDA support:** +2. **Sync the environment:** -```bash -pip install torch==2.7.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126 -``` - -3. **Clone the repository and install the package:** +This will create a virtual environment, install Python 3.12, PyTorch 2.7.0 (with CUDA 12.6), and all project dependencies. ```bash -git clone https://github.com/facebookresearch/sam3.git -cd sam3 -pip install -e . +uv sync --extra notebooks --extra train --extra dev ``` -4. **Install additional dependencies for example notebooks or development:** +3. **Verify installation:** ```bash -# For running example notebooks -pip install -e ".[notebooks]" - -# For development -pip install -e ".[train,dev]" +uv run python -c "import torch; import sam3; print('Installation successful!')" ``` ## Getting Started ⚠️ Before using SAM 3, please request access to the checkpoints on the SAM 3 Hugging Face [repo](https://huggingface.co/facebook/sam3). Once accepted, you -need to be authenticated to download the checkpoints. You can do this by running -the following [steps](https://huggingface.co/docs/huggingface_hub/en/quick-start#authentication) -(e.g. `hf auth login` after generating an access token.) +need to be authenticated to download the checkpoints. You can do this by running: + +```bash +uv run huggingface-cli login +``` + +and pasting your access token from [your settings](https://huggingface.co/settings/tokens). ### Basic Usage @@ -174,11 +167,8 @@ dataset. To run the Jupyter notebook examples: ```bash -# Make sure you have the notebooks dependencies installed -pip install -e ".[notebooks]" - -# Start Jupyter notebook -jupyter notebook examples/sam3_image_predictor_example.ipynb +# Start Jupyter notebook (notebooks dependencies are installed via uv sync) +uv run jupyter notebook examples/sam3_image_predictor_example.ipynb ``` ## Model @@ -347,13 +337,13 @@ We release 2 image benchmarks, [SA-Co/Gold](scripts/eval/gold/README.md) and To set up the development environment: ```bash -pip install -e ".[dev,train]" +uv sync --extra dev --extra train ``` To format the code: ```bash -ufmt format . +uv run ufmt format . ``` ## Contributing diff --git a/README_TRAIN.md b/README_TRAIN.md index 01904c27..a7e41a9f 100644 --- a/README_TRAIN.md +++ b/README_TRAIN.md @@ -7,7 +7,7 @@ This repository supports finetuning SAM3 models on custom datasets in multi-node ```bash cd sam3 -pip install -e ".[train]" +uv sync --extra train ``` ### Training Script Usage diff --git a/examples/sam3_image_predictor_example.ipynb b/examples/sam3_image_predictor_example.ipynb index 5ac2b6fc..8c704dc6 100644 --- a/examples/sam3_image_predictor_example.ipynb +++ b/examples/sam3_image_predictor_example.ipynb @@ -108,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "output": { "id": 785101161160169, @@ -116,10 +116,7 @@ } }, "outputs": [], - "source": [ - "bpe_path = f\"{sam3_root}/assets/bpe_simple_vocab_16e6.txt.gz\"\n", - "model = build_sam3_image_model(bpe_path=bpe_path)" - ] + "source": "model = build_sam3_image_model()" }, { "cell_type": "code", @@ -371,4 +368,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/examples/sample_run.py b/examples/sample_run.py new file mode 100644 index 00000000..16012275 --- /dev/null +++ b/examples/sample_run.py @@ -0,0 +1,59 @@ + +import os +import torch +import numpy as np +from PIL import Image +from sam3.model_builder import build_sam3_image_model +from sam3.model.sam3_image_processor import Sam3Processor + +def run_sample(): + print("Setting up SAM3...") + + # Check if assets exist + # Updated to look one directory up for assets since this is in examples/ + image_path = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "assets/images/test_image.jpg") + + if not os.path.exists(image_path): + print(f"Warning: {image_path} not found. Please ensure the assets directory exists.") + return + + try: + # Load the model + print("Loading SAM3 model (this may trigger checkpoint download)...") + model = build_sam3_image_model() + # Lower confidence threshold from default 0.5 to detect more objects + processor = Sam3Processor(model, confidence_threshold=0.1) + + # Load an image + print(f"Loading image from {image_path}...") + image = Image.open(image_path) + + # Run inference + print("Running inference...") + inference_state = processor.set_image(image) + + # Prompt the model + prompt_text = "kid wearing a red bib" + print(f"Prompting with: '{prompt_text}'") + output = processor.set_text_prompt(state=inference_state, prompt=prompt_text) + + # Get results + masks = output["masks"] + boxes = output["boxes"] + scores = output["scores"] + + print("\nSuccess!") + print(f"Found {len(masks)} masks.") + print(f"Scores: {scores[:5]} (showing top 5)") + print(f"Masks shape: {masks.shape}") + + except Exception as e: + print("\nError occurred:") + print(str(e)) + if "huggingface" in str(e).lower() or "unauthorized" in str(e).lower() or "login" in str(e).lower(): + print("\nIt looks like an authentication error.") + print("Please run: uv run huggingface-cli login") + print("And paste your token from https://huggingface.co/settings/tokens") + +if __name__ == "__main__": + run_sample() diff --git a/pyproject.toml b/pyproject.toml index 86ae1951..1afa363e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,7 +7,7 @@ name = "sam3" dynamic = ["version"] description = "SAM3 (Segment Anything Model 3) implementation" readme = "README.md" -requires-python = ">=3.8" +requires-python = ">=3.9" license = {file = "LICENSE"} authors = [ {name = "Meta AI Research"} @@ -33,6 +33,9 @@ dependencies = [ "iopath>=0.1.10", "typing_extensions", "huggingface_hub", + "torch==2.7.0", + "torchvision>=0.22.0", + "torchaudio>=2.7.0", ] [project.optional-dependencies] @@ -133,3 +136,6 @@ testpaths = ["tests"] python_files = "test_*.py" 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