mirror of
https://github.com/imgproxy/imgproxy.git
synced 2025-02-02 11:34:20 +02:00
5af61b2be8
* Update autoquality.md * Update best_format.md * Update chained_pipelines.md * Update chaining_the_processing.md * Update encrypting_the_source_url.md * Update getting_the_image_info.md * Update object_detection.md
42 lines
1.9 KiB
Markdown
42 lines
1.9 KiB
Markdown
# Object detection
|
|
|
|
imgproxy can detect objects on the image and use them for smart cropping, bluring the detections, or drawing the detections.
|
|
|
|
For object detection purposes, imgproxy uses the [Darknet YOLO](https://github.com/AlexeyAB/darknet) model. We provide Docker images with a model trained for face detection, but you can use any Darknet YOLO model found in the [zoo](https://github.com/AlexeyAB/darknet/wiki/YOLOv4-model-zoo) or you can train your own model by following this [guide](https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects).
|
|
|
|
## Configuration
|
|
|
|
You need to define four config variables to enable object detection:
|
|
|
|
* `IMGPROXY_OBJECT_DETECTION_CONFIG`: a path to the neural network config
|
|
* `IMGPROXY_OBJECT_DETECTION_WEIGHTS`: a path to the neural network weights
|
|
* `IMGPROXY_OBJECT_DETECTION_CLASSES`: a path to the text file with the classes names, one per line
|
|
* `IMGPROXY_OBJECT_DETECTION_NET_SIZE`: the size of the neural network input. The width and the heights of the inputs should be the same, so this config value should be a single number. Default: 416
|
|
|
|
Read the [configuration guide](configuration.md#object-detection) for more config values info.
|
|
|
|
## Usage examples
|
|
### Object-oriented crop
|
|
|
|
You can [crop](https://docs.imgproxy.net/generating_the_url?id=crop) your images and keep objects of desired classes in frame:
|
|
|
|
```
|
|
.../crop:256:256/g:obj:face/...
|
|
```
|
|
|
|
### Bluring detections
|
|
|
|
You can [blur objects](https://docs.imgproxy.net/generating_the_url?id=blur-detections) of desired classes, thus making anonymization or hiding NSFW content possible:
|
|
|
|
```
|
|
.../blur_detections:7:face/...
|
|
```
|
|
|
|
### Draw detections
|
|
|
|
You can make imgproxy [draw bounding boxes](https://docs.imgproxy.net/generating_the_url?id=draw-detections) for the detected objects of the desired classes (this is handy for testing your models):
|
|
|
|
```
|
|
.../draw_detections:1:face/...
|
|
```
|