diff --git a/examples/vggt/depth.dora-session.yaml b/examples/vggt/depth.dora-session.yaml new file mode 100644 index 00000000..13428f1b --- /dev/null +++ b/examples/vggt/depth.dora-session.yaml @@ -0,0 +1,8 @@ +build_id: 2b402c1e-e52e-45e9-86e5-236b33a77369 +session_id: 275de19c-e605-4865-bc5f-2f15916bade9 +git_sources: {} +local_build: + node_working_dirs: + camera: /Users/xaviertao/Documents/work/dora/examples/vggt + dora-vggt: /Users/xaviertao/Documents/work/dora/examples/vggt + plot: /Users/xaviertao/Documents/work/dora/examples/vggt diff --git a/examples/vggt/depth.yaml b/examples/vggt/depth.yaml new file mode 100644 index 00000000..2013aa60 --- /dev/null +++ b/examples/vggt/depth.yaml @@ -0,0 +1,26 @@ +nodes: + - id: camera + build: pip install opencv-video-capture + path: opencv-video-capture + inputs: + tick: dora/timer/millis/100 + outputs: + - image + env: + CAPTURE_PATH: 1 + + - id: dora-vggt + build: pip install -e ../../node-hub/dora-vggt + path: dora-vggt + inputs: + image: camera/image + outputs: + - depth + - image + + - id: plot + build: pip install dora-rerun + path: dora-rerun + inputs: + camera/image: dora-vggt/image + camera/depth: dora-vggt/depth diff --git a/libraries/arrow-convert/src/lib.rs b/libraries/arrow-convert/src/lib.rs index cf293161..f9b8f21e 100644 --- a/libraries/arrow-convert/src/lib.rs +++ b/libraries/arrow-convert/src/lib.rs @@ -1,4 +1,7 @@ -use arrow::array::{Array, Float32Array, Float64Array, Int32Array, Int64Array, UInt32Array}; +use arrow::array::{ + Array, Float32Array, Float64Array, Int16Array, Int32Array, Int64Array, Int8Array, UInt16Array, + UInt32Array, UInt8Array, +}; use arrow::datatypes::DataType; use eyre::{eyre, ContextCompat, Result}; use num::NumCast; @@ -63,7 +66,11 @@ macro_rules! register_array_handlers { register_array_handlers! { (DataType::Float32, Float32Array, "float32"), (DataType::Float64, Float64Array, "float64"), + (DataType::Int8, Int8Array, "int8"), + (DataType::Int16, Int16Array, "int16"), (DataType::Int32, Int32Array, "int32"), (DataType::Int64, Int64Array, "int64"), + (DataType::UInt8, UInt8Array, "uint8"), + (DataType::UInt16, UInt16Array, "uint16"), (DataType::UInt32, UInt32Array, "uint32"), } diff --git a/node-hub/dora-vggt/README.md b/node-hub/dora-vggt/README.md new file mode 100644 index 00000000..38179a7b --- /dev/null +++ b/node-hub/dora-vggt/README.md @@ -0,0 +1,40 @@ +# dora-vggt + +## Getting started + +- Install it with uv: + +```bash +uv venv -p 3.11 --seed +uv pip install -e . +``` + +## Contribution Guide + +- Format with [ruff](https://docs.astral.sh/ruff/): + +```bash +uv pip install ruff +uv run ruff check . --fix +``` + +- Lint with ruff: + +```bash +uv run ruff check . +``` + +- Test with [pytest](https://github.com/pytest-dev/pytest) + +```bash +uv pip install pytest +uv run pytest . # Test +``` + +## YAML Specification + +## Examples + +## License + +dora-vggt's code are released under the MIT License diff --git a/node-hub/dora-vggt/dora_vggt/__init__.py b/node-hub/dora-vggt/dora_vggt/__init__.py new file mode 100644 index 00000000..79cbf370 --- /dev/null +++ b/node-hub/dora-vggt/dora_vggt/__init__.py @@ -0,0 +1,13 @@ +"""TODO: Add docstring.""" + +import os + +# Define the path to the README file relative to the package directory +readme_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "README.md") + +# Read the content of the README file +try: + with open(readme_path, encoding="utf-8") as f: + __doc__ = f.read() +except FileNotFoundError: + __doc__ = "README file not found." diff --git a/node-hub/dora-vggt/dora_vggt/__main__.py b/node-hub/dora-vggt/dora_vggt/__main__.py new file mode 100644 index 00000000..51a1554d --- /dev/null +++ b/node-hub/dora-vggt/dora_vggt/__main__.py @@ -0,0 +1,6 @@ +"""TODO: Add docstring.""" + +from .main import main + +if __name__ == "__main__": + main() diff --git a/node-hub/dora-vggt/dora_vggt/main.py b/node-hub/dora-vggt/dora_vggt/main.py new file mode 100644 index 00000000..32aad2ae --- /dev/null +++ b/node-hub/dora-vggt/dora_vggt/main.py @@ -0,0 +1,142 @@ +"""TODO: Add docstring.""" + +import io +from collections import deque as Deque + +import cv2 +import numpy as np +import pyarrow as pa +import torch +from dora import Node +from PIL import Image +from vggt.models.vggt import VGGT +from vggt.utils.load_fn import load_and_preprocess_images +from vggt.utils.pose_enc import pose_encoding_to_extri_intri + +# bfloat16 is supported on Ampere GPUs (Compute Capability 8.0+) +dtype = torch.float16 + +# Initialize the model and load the pretrained weights. +# This will automatically download the model weights the first time it's run, which may take a while. +model = VGGT.from_pretrained("facebook/VGGT-1B") +model.eval() + +# Import vecdeque + + +def main(): + """TODO: Add docstring.""" + node = Node() + raw_images = Deque(maxlen=5) + + for event in node: + if event["type"] == "INPUT": + if event["id"] == "TICK": + print( + f"""Node received: + id: {event["id"]}, + value: {event["value"]}, + metadata: {event["metadata"]}""", + ) + + if "image" in event["id"]: + storage = event["value"] + metadata = event["metadata"] + encoding = metadata["encoding"] + width = metadata["width"] + height = metadata["height"] + + if ( + encoding == "bgr8" + or encoding == "rgb8" + or encoding in ["jpeg", "jpg", "jpe", "bmp", "webp", "png"] + ): + channels = 3 + storage_type = np.uint8 + else: + raise RuntimeError(f"Unsupported image encoding: {encoding}") + + if encoding == "bgr8": + frame = ( + storage.to_numpy() + .astype(storage_type) + .reshape((height, width, channels)) + ) + frame = frame[:, :, ::-1] # OpenCV image (BGR to RGB) + elif encoding == "rgb8": + frame = ( + storage.to_numpy() + .astype(storage_type) + .reshape((height, width, channels)) + ) + elif encoding in ["jpeg", "jpg", "jpe", "bmp", "webp", "png"]: + storage = storage.to_numpy() + frame = cv2.imdecode(storage, cv2.IMREAD_COLOR) + frame = frame[:, :, ::-1] # OpenCV image (BGR to RGB) + else: + raise RuntimeError(f"Unsupported image encoding: {encoding}") + image = Image.fromarray(frame) + + # Save the image to a bytes buffer + buffer = io.BytesIO() + image.save(buffer, format="JPEG") # or JPEG, etc. + + # Rewind the buffer's file pointer to the beginning + buffer.seek(0) + raw_images.append(buffer) + + with torch.no_grad(): + images = load_and_preprocess_images(raw_images) + + images = images[None] # add batch dimension + aggregated_tokens_list, ps_idx = model.aggregator(images) + # Predict Cameras + pose_enc = model.camera_head(aggregated_tokens_list)[-1] + # Extrinsic and intrinsic matrices, following OpenCV convention (camera from world) + extrinsic, intrinsic = pose_encoding_to_extri_intri( + pose_enc, images.shape[-2:] + ) + + # Predict Depth Maps + depth_map, depth_conf = model.depth_head( + aggregated_tokens_list, images, ps_idx + ) + print(depth_conf.max()) + depth_map[depth_conf < 1.0] = 0.0 # Set low confidence pixels to 0 + depth_map = depth_map.to(torch.float64) + + depth_map = depth_map[-1][-1].cpu().numpy() + + # Warning: Make sure to add my_output_id and my_input_id within the dataflow. + node.send_output( + output_id="depth", + data=pa.array(depth_map.ravel()), + metadata={ + "width": depth_map.shape[1], + "height": depth_map.shape[0], + }, + ) + + image = images[-1][-1].cpu().numpy() * 255 + image = image.astype(np.uint8) + # reorder pixels to be in last dimension + image = image.transpose(1, 2, 0) + + print( + f"Image shape: {image.shape}, dtype: {image.dtype} and depth map shape: {depth_map.shape}, dtype: {depth_map.dtype}" + ) + + # Warning: Make sure to add my_output_id and my_input_id within the dataflow. + node.send_output( + output_id="image", + data=pa.array(image.ravel()), + metadata={ + "encoding": "rgb8", + "width": image.shape[1], + "height": image.shape[0], + }, + ) + + +if __name__ == "__main__": + main() diff --git a/node-hub/dora-vggt/pyproject.toml b/node-hub/dora-vggt/pyproject.toml new file mode 100644 index 00000000..a2cda1b1 --- /dev/null +++ b/node-hub/dora-vggt/pyproject.toml @@ -0,0 +1,30 @@ +[project] +name = "dora-vggt" +version = "0.0.0" +authors = [{ name = "Your Name", email = "email@email.com" }] +description = "dora-vggt" +license = { text = "MIT" } +readme = "README.md" +requires-python = ">=3.10" + +dependencies = [ + "dora-rs >= 0.3.9", + "torch>=2.7.0", + "torchvision>=0.22.0", + "vggt", +] + +[dependency-groups] +dev = ["pytest >=8.1.1", "ruff >=0.9.1"] + +[project.scripts] +dora-vggt = "dora_vggt.main:main" + +[tool.ruff.lint] +extend-select = [ + "D", # pydocstyle + "UP", +] + +[tool.uv.sources] +vggt = { git = "https://github.com/facebookresearch/vggt" } diff --git a/node-hub/dora-vggt/tests/test_dora_vggt.py b/node-hub/dora-vggt/tests/test_dora_vggt.py new file mode 100644 index 00000000..19bc6001 --- /dev/null +++ b/node-hub/dora-vggt/tests/test_dora_vggt.py @@ -0,0 +1,13 @@ +"""Test module for dora_vggt package.""" + +import pytest + + +def test_import_main(): + """Test importing and running the main function.""" + from dora_vggt.main import main + + # Check that everything is working, and catch Dora RuntimeError + # as we're not running in a Dora dataflow. + with pytest.raises(RuntimeError): + main() diff --git a/node-hub/dora-vggt/uv.lock b/node-hub/dora-vggt/uv.lock new file mode 100644 index 00000000..478d5153 --- /dev/null +++ b/node-hub/dora-vggt/uv.lock @@ -0,0 +1,1009 @@ +version = 1 +requires-python = ">=3.10" +resolution-markers = [ + "python_full_version < '3.11' and platform_system == 'Darwin'", + "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux'", + "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system == 'Linux') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux')", + "python_full_version == '3.11.*' and platform_system == 'Darwin'", + 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