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c887fd3
refactor: Complete visengine to visdet namespace migration and fix bugs
GeorgePearse Dec 2, 2025
c9f680b
docs: Add roadmap with SPDL integration plan
GeorgePearse Dec 2, 2025
6cbe4da
feat(tools): Add Modal script to download COCO 2017 dataset
GeorgePearse Dec 23, 2025
273d49d
Merge pull request #1052 from BinItAI/feature/coco-on-modal
GeorgePearse Dec 23, 2025
12064c9
chore: Remove zuban type checker temporarily
GeorgePearse Dec 23, 2025
468d808
fix: Import cv transforms and restore expected transform behaviors
GeorgePearse Dec 23, 2025
0ba44ad
Merge pull request #1054 from BinItAI/chore/remove-zuban
GeorgePearse Dec 23, 2025
bf428a8
chore: add scoped zuban typecheck for structures
GeorgePearse Dec 23, 2025
2080e30
Merge pull request #1055 from BinItAI/chore/zuban-typecheck-structures
GeorgePearse Dec 23, 2025
9983698
chore: add scoped zuban typecheck for visdet/apis
GeorgePearse Dec 23, 2025
506acc0
Merge pull request #1056 from BinItAI/chore/zuban-typecheck-apis
GeorgePearse Dec 23, 2025
6bb1699
chore: add scoped zuban typecheck for visdet/core/mask
GeorgePearse Dec 23, 2025
2415766
docs: add tests status badge
GeorgePearse Dec 23, 2025
fcfe9d7
Merge pull request #1063 from BinItAI/chore/tests-passing-badge
GeorgePearse Dec 24, 2025
ee97527
Merge pull request #1057 from BinItAI/chore/zuban-typecheck-core-mask
GeorgePearse Dec 24, 2025
9451055
Export load_yaml_config from config module
GeorgePearse Oct 26, 2025
e1ff6fc
Export Config from visdet.engine
GeorgePearse Oct 26, 2025
df0dbfc
Export DefaultScope from visdet.engine
GeorgePearse Oct 26, 2025
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34 changes: 25 additions & 9 deletions .pre-commit-config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -37,21 +37,37 @@ repos:
stages: [pre-commit]
pass_filenames: false

- repo: https://github.com/kynan/nbstripout
rev: 0.8.1
hooks:
- id: nbstripout

# Zuban type checker
# Zuban type checker (scoped to a single directory)
- repo: local
hooks:
- id: zuban
name: Zuban type checker
entry: uv run zuban check
name: Zuban type checker (visdet/structures)
entry: uv run zuban check visdet/structures
language: system
types: [python]
pass_filenames: false
files: ^visdet/structures/

- id: zuban-apis
name: Zuban type checker (visdet/apis)
entry: uv run zuban check visdet/apis
language: system
types: [python]
pass_filenames: false
exclude: ^(archive|tests|configs)/
files: ^visdet/apis/

- id: zuban-core-mask
name: Zuban type checker (visdet/core/mask)
entry: uv run zuban check visdet/core/mask
language: system
types: [python]
pass_filenames: false
files: ^visdet/core/mask/

- repo: https://github.com/kynan/nbstripout
rev: 0.8.1
hooks:
- id: nbstripout

# Block old-style viscv/visengine imports
- repo: local
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1 change: 1 addition & 0 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@

<p>
<a href="https://pypi.org/project/visdet"><img src="https://img.shields.io/pypi/v/visdet?style=flat-square&color=blue" alt="PyPI"/></a>
<a href="https://github.com/BinItAI/visdet/actions/workflows/test.yml"><img src="https://img.shields.io/github/actions/workflow/status/BinItAI/visdet/test.yml?branch=main&style=flat-square" alt="Tests"/></a>
<a href="https://binitai.github.io/visdet/"><img src="https://img.shields.io/badge/docs-latest-brightgreen?style=flat-square" alt="Documentation"/></a>
</p>

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4 changes: 2 additions & 2 deletions configs/presets/datasets/coco_instance_segmentation.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -9,12 +9,12 @@ type: CocoDataset
data_root: data/coco/
ann_file: annotations/instances_train2017.json
data_prefix:
img: train2017/
img_path: train2017/

# Validation paths
val_ann_file: annotations/instances_val2017.json
val_data_prefix:
img: val2017/
img_path: val2017/

# Data pipeline for training
train_pipeline:
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25 changes: 21 additions & 4 deletions docs/getting-started/quick-start.md
Original file line number Diff line number Diff line change
Expand Up @@ -2,19 +2,36 @@

This guide provides quick examples to get you started with VisDet.

## Training with SimpleRunner

The easiest way to train a model is using the `SimpleRunner` API:

```python
from visdet import SimpleRunner

# Simple, string-based API - just like Hugging Face or Ultralytics
runner = SimpleRunner(
model='mask_rcnn_swin_s',
dataset='coco_instance_segmentation',
epochs=12,
batch_size=2
)

runner.train()
```

## Inference with Pre-trained Models

### Using High-level APIs

You can use high-level APIs to perform inference on images:

```python
from mmdet.apis import init_detector, inference_detector
import mmcv
from visdet.apis import init_detector, inference_detector

# Specify the config file and checkpoint file
config_file = 'configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
checkpoint_file = 'checkpoints/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth'
checkpoint_file = 'checkpoints/faster_rcnn_r50_fpn_1x_coco.pth'

# Build the model from a config file and a checkpoint file
model = init_detector(config_file, checkpoint_file, device='cuda:0')
Expand All @@ -24,7 +41,7 @@ img = 'demo/demo.jpg'
result = inference_detector(model, img)

# Show the results
from mmdet.apis import show_result_pyplot
from visdet.apis import show_result_pyplot
show_result_pyplot(model, img, result)
```

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7 changes: 7 additions & 0 deletions docs/index.md
Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,13 @@ The master branch works with **PyTorch 1.5+**.

</details>

## Roadmap

See our [Roadmap](roadmap.md) for planned features, including:
- **SPDL Integration**: Thread-based data loading for 74% faster training
- **Kornia**: GPU-accelerated augmentations
- **Python 3.13t**: Free-threaded Python support

## What's New

For the latest updates and improvements to VisDet, please refer to the [changelog](about/changelog.md).
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