Autodistill DETR Module
This repository contains the code supporting the DETR base model for use with Autodistill.
DETR is a transformer-based computer vision model you can use for object detection. Autodistill supports training a model using the Meta Research Resnet 50 checkpoint.
Read the full Autodistill documentation.
Read the DETR Autodistill documentation.
Installation
To use DETR with autodistill, you need to install the following dependency:
pip3 install autodistill-detr
Quickstart
from autodistill_detr import DETR
# load the model
target_model = DETR()
# train for 10 epochs
target_model.train("./roads", epochs=10)
# run inference on an image
target_model.predict("./roads/valid/-3-_jpg.rf.bee113a09b22282980c289842aedfc4a.jpg")
License
This project is licensed under an Apache 2.0 license. See the Hugging Face model card for the DETR Resnet 50 model for more information on the model license.
🏆 Contributing
We love your input! Please see the core Autodistill contributing guide to get started. Thank you 🙏 to all our contributors!
Release files for autodistill-detr 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| autodistill-detr-0.1.1.tar.gz | 8.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autodistill_detr-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.7 kB
Release files / autodistill-detr-0.1.1.tar.gz
| Download URL | autodistill-detr-0.1.1.tar.gz |
|---|---|
| Size | 8.2 kB |
| Tags | Source |
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Release files / autodistill_detr-0.1.1-py3-none-any.whl
| Download URL | autodistill_detr-0.1.1-py3-none-any.whl |
|---|---|
| Size | 8.6 kB |
| Tags | Python 3 |
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