This is a repository to play with OpenCV and yolo object detection model
Inspired by:
- Java 20
- A default video camera (for demo purposes)
- If using CUDA, you will need the appropriate GPU with the correct drivers
- Docker, if you wish to run a local rtmp server
First run
$ ./mvnw clean install
And execute with
$ ./mvnw exec:java
You should see an Canvas Frame appearing
In order to use object detection, download the official YOLOv7 files Once downloaded put them at the root of the project this way
model/yolov7/config.cfg
model/yolov7/names.txt
model/yolov7/weights.weights
Then execute:
$ ./mvnw exec:java "-Dexec.args=--yolo-enabled --cuda-enabled"
If you wish to set your own path you can set it with the --yolo-path option
You can read/write from a rtmp stream using respectively the option
--input-type=stream --output-type=stream
In order to read from a rtmp server or to stream on it you can use this project: nginx-rtmp-docker
Start the project in a container this way:
docker run -it --cpus 1 --memory 512m -p 1935:1935 -p 8080:80 --rm alfg/nginx-rtmp
Then:
- push streaming content to your server:
$ ./mvnw exec:java "-Dexec.args=--output-type=stream"
- read that content, apply object detection and display it:
$ ./mvnw exec:java "-Dexec.args=--input-type=stream --yolo-enabled --cuda-enabled"
You should see the content streamed from your webcam
Usage: <main class> [--cuda-enabled] [--yolo-enabled]
[--confidence-threshold=<confidenceThreshold>]
[--gop=<gop>] [--in-address=<inputAddress>]
[--in-bitrate=<inputBitrate>] [--in-codec=<inputCodec>]
[--in-crf=<inputCrf>] [--in-format=<inputFormat>]
[--in-frame-rate=<inputFrameRate>]
[--in-height=<inputHeight>] [--in-preset=<inputPreset>]
[--in-tune=<inputTune>] [--in-type=<inputType>]
[--in-width=<inputWidth>] [--model-format=<modelFormat>]
[--nms-threshold=<nmsThreshold>]
[--out-address=<outputAddress>]
[--out-bitrate=<outputBitrate>] [--out-codec=<outputCodec>]
[--out-crf=<outputCrf>] [--out-format=<outputFormat>]
[--out-frame-rate=<outputFrameRate>]
[--out-height=<outputHeight>] [--out-preset=<outputPreset>]
[--out-tune=<outputTune>] [--out-type=<outputType>]
[--out-width=<outputWidth>] [--yolo-height=<yoloHeight>]
[--yolo-path=<modelPath>] [--yolo-width=<yoloWidth>]
--confidence-threshold=<confidenceThreshold>
the confidence detection threshold
default: 0.4
--cuda-enabled enables cuda detection if present
fallbacks to CPU otherwise
Default: false
--gop=<gop> The output GOP (Group Of Pictures) size of the
stream
Default: 60
--in-address=<inputAddress>
The input address to use when fetching from a URL
The URL depends on the forman (flv, mjpeg, ...) and
is optional if using --in-type=direct
Default: rtmp://localhost:1935/stream/hello
--in-bitrate=<inputBitrate>
The input bitrate of the stream
Default: 2000000
--in-codec=<inputCodec>
The input codec of the stream (default:
AV_CODEC_ID_H264)
--in-crf=<inputCrf> The input crf of the stream
Default: 28
--in-format=<inputFormat>
The input format of the stream
Default: flv
--in-frame-rate=<inputFrameRate>
The input frame rate of the stream
Default: 60
--in-height=<inputHeight>
The input height of the stream
Default: 720
--in-preset=<inputPreset>
The input preset of the stream
Default: ultrafast
--in-tune=<inputTune> The input tune of the stream
Default: zerolatency
--in-type=<inputType> The input type of the stream
Default: DIRECT
--in-width=<inputWidth>
The input width of the stream
Default: 1280
--model-format=<modelFormat>
enables yolo detection on the stream
default: DARKNET
Default: DARKNET
--nms-threshold=<nmsThreshold>
the NMS (Non-maximum Suppression) threshold
more info: https://arxiv.org/abs/1705.02950
Default: 0.4
--out-address=<outputAddress>
The output address to use when streaming on a URL
The URL depends on the format (flv, mjpeg, ...) and
is optional if using --out-type=direct
Default: rtmp://localhost:1935/stream/hello
--out-bitrate=<outputBitrate>
The output bitrate of the stream
Default: 2000000
--out-codec=<outputCodec>
The output codec of the stream (default)
--out-crf=<outputCrf> The output crf of the stream
Default: 28
--out-format=<outputFormat>
The output format of the stream
Default: flv
--out-frame-rate=<outputFrameRate>
The output framerate of the stream
Default: 60
--out-height=<outputHeight>
The output height of the stream
Default: 720
--out-preset=<outputPreset>
The output preset of the stream
Default: ultrafast
--out-tune=<outputTune>
The output tune of the stream
Default: zerolatency
--out-type=<outputType>
The output type of the stream
Default: DIRECT
--out-width=<outputWidth>
The output width of the stream
Default: 1280
--yolo-enabled enables yolo detection on the stream
default: false
Default: false
--yolo-height=<yoloHeight>
the yolo image blob height used for detection
Default: 608
--yolo-path=<modelPath>
path to the yolo files
the files within that folder must be named: config.
cfg, names.txt, weights.weights
eg: /path/to/yolov7 is the path that will contain:
/path/to/yolov7/config.cfg, /path/to/yolov7/names.
txt, /path/to/yolov7/weights.weights
--yolo-width=<yoloWidth>
the yolo image blob width used for detection