A solution to the task given by the Oberseminar of Messtechnik Institute of TU Dresden in 2021
please install on a linux operating system
git clone https://github.com/Anxum/NeuroFind.git
cd NeuroFind
git clone https://github.com/ultralytics/yolov5.git temp
mv temp/.git yolov5/.git
mv temp/* yolov5
rm -rf temp
cd yolov5
pip3 install -r requirements.txt
cd ../Faster_R-CNN
git clone https://github.com/tensorflow/models.git
pip3 install lxml
mkdir models/protoc
mv protoc-3.19.3-linux-x86_64.zip models/protoc
cd models/protoc
unzip protoc-3.19.3-linux-x86_64.zip
rm -r protoc-3.19.3-linux-x86_64.zip
cd ../research
../protoc/bin/protoc object_detection/protos/*.proto --python_out=.
export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim
cp object_detection/packages/tf2/setup.py .
python3 -m pip install --use-feature=2020-resolver .
cd ../../../..
git clone https://github.com/Anxum/NeuroFind.git
cd NeuroFind
git clone https://github.com/ultralytics/yolov5.git temp
mv temp/.git yolov5/.git
mv temp/* yolov5
rm -rf temp
cd yolov5
pip3 install -r requirements.txt
cd ../..
git clone https://github.com/Anxum/NeuroFind.git
cd NeuroFind/Faster_R-CNN
git clone https://github.com/tensorflow/models.git
pip3 install lxml
mkdir models/protoc
mv protoc-3.19.3-linux-x86_64.zip models/protoc
cd models/protoc
unzip protoc-3.19.3-linux-x86_64.zip
rm -r protoc-3.19.3-linux-x86_64.zip
cd ../research
../protoc/bin/protoc object_detection/protos/*.proto --python_out=.
export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim
cp object_detection/packages/tf2/setup.py .
python3 -m pip install --use-feature=2020-resolver .
cd ../../../..
In addition to the installation guide above please download the weights for the neuronal networks from: --insert url--
Standardized paths for YOLOv5 and Faster R-CNN:
| Neuronal Network | Put Weights to: |
|---|---|
| YOLOv5 | NeuroFind/yolov5/runs/train/weights |
| Faster R-CNN | NeuroFind/Faster_R-CNN/export |
If you choose to put the weights into another folder you must refer to these paths if you wish to use the inference algorithms later.
Please download weigts first as described above or train the network yourself before Inference
For Inference please run (from NeuroFind/yolov5)
python3 yolo_detect.py
Possible arguments include:
| Argument | Description | Input format | Default Value | Comment |
|---|---|---|---|---|
| --weights | Put path to weights | OS_PATH | ./runs/train/weights/best.pt | |
| --source | path to file or dir | OS_PATH | ../Images | URL, glob and webcam(0) could be possible, not tested |
| --conf-thres | minimal value of confidence for bounding boxes | float, [0..1] | 0.25 | |
| --device | Specify the device to run Inference | 0,1,2,3,..., cpu for CPU | ||
| --nosave | Don't save the images after inference | False | ||
| --project | Save to project/name | OS_PATH | ./runs/detect | |
| --name | Save to project/name | str | exp | |
| --line-thickness | Thickness of lines of bounding boxes on the image | int | 2 |
Arguments that are not tested or will not work or should not be specified
| Not testet | Will not work | Please don't use |
|---|---|---|
| --exist-ok | --visualize | --hide labels |
| --classes | --view-img | --hide-conf |
| --half | --save-conf | |
| --dnn | --imgsz | |
| --update | --save-txt | |
| --augment | ||
| --agnostic-nms | ||
| --iou-thres | ||
| --max-det |
For Inference please run (from NeuroFind/Faster_R-CNN)
python3 frcnn_detect.py
Possible arguments include:
| Argument | Description | Input format | Default Value |
|---|---|---|---|
| --config | Put path to config | OS_PATH | ./export/pipeline.config |
| --source | path to file or dir | OS_PATH | ../Images |
| --checkpt | Path to checkpoint | OS_PATH | ./export/checkpoint/ckpt-0 |
| --labelmap | Path to labelmap | OS_PATH | ./export/label_map.pbtxt |
| --conf-thres | minimal value of confidence for bounding boxes | float, [0..1] | 0.25 |
| --output | Save files to this path | OS_PATH | ./runs/detect/exp |
| --nosave | Don't save the images after inference | False | |
| --line-thickness | Thickness of lines of bounding boxes on the image | int | 2 |
to create a training dataset please use( in NeuroFind/training_data_yolo):
python3 crop_image.py
For training, please refer to: https://github.com/ultralytics/yolov5.git
For training, please refer to: https://github.com/tensorflow/models.git