MMDetection
v2.8.0
Get Started
Prerequisites
Installation
Verification
Model Zoo Statistics
Benchmark and Model Zoo
Quick Run
1: Inference and train with existing models and standard datasets
2: Train with customized datasets
Tutorials
Tutorial 1: Learn about Configs
Tutorial 2: Customize Datasets
Tutorial 3: Customize Data Pipelines
Tutorial 4: Customize Models
Tutorial 5: Customize Runtime Settings
Tutorial 6: Customize Losses
Tutorial 7: Finetuning Models
Tutorial 8: Pytorch to ONNX (Experimental)
Useful Tools and Scripts
Log Analysis
Visualization
Error Analysis
Model Complexity
Model conversion
Dataset Conversion
Miscellaneous
Notes
Conventions
Compatibility with MMDetection 1.x
Projects based on MMDetection
Changelog
MMCV Installation
PyTorch/CUDA Environment
Training
API Reference
API Reference
MMDetection
Docs
»
<no title>
Edit on GitHub
Tutorial 1: Learn about Configs
Modify config through script arguments
Config File Structure
Config Name Style
An Example of Mask R-CNN
FAQ
Tutorial 2: Customize Datasets
Support new data format
Customize datasets by dataset wrappers
Modify Dataset Classes
Tutorial 3: Customize Data Pipelines
Design of Data pipelines
Extend and use custom pipelines
Tutorial 4: Customize Models
Develop new components
Tutorial 5: Customize Runtime Settings
Customize optimization settings
Customize training schedules
Customize workflow
Customize hooks
Tutorial 6: Customize Losses
Computation pipeline of a loss
Tweaking loss
Weighting loss (step 2)
Tutorial 7: Finetuning Models
Inherit base configs
Modify head
Modify dataset
Modify training schedule
Use pre-trained model
Tutorial 8: Pytorch to ONNX (Experimental)
How to convert models from Pytorch to ONNX
List of supported models exportable to ONNX
Reminders
FAQs
Read the Docs
v: v2.8.0
Versions
latest
stable
v2.8.0
v2.7.0
v2.6.0
v2.5.0
v2.4.0
v2.3.0
v2.2.1
v2.2.0
v2.1.0
v2.0.0
v1.2.0
Downloads
On Read the Docs
Project Home
Builds
Free document hosting provided by
Read the Docs
.