/kiwi-detection

YOLOV3 & Tensorflow kiwi detection and for Kiwi fruit detection and harvesting

Primary LanguagePython

YOLOV3 & Tensorflow kiwi detection and for Kiwi fruit detection and harvesting

Yolov3 is an algorithm that uses deep convolutional neural networks to perform object detection. This repository implements Yolov3 using TensorFlow


Saving your yolov3 weights as a TensorFlow model.

Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!

# yolov3
python load_weights.py

After executing one of the above lines, you should see .tf files in your weights folder.

Running just the TensorFlow model

The tensorflow model can also be run not using the APIs but through using detect.py script.

Don't forget to set the IoU (Intersection over Union) and Confidence Thresholds within your yolov3-tf2/models.py file

Usage examples

Let's run an example or two using sample images found within the data/images folder.

# yolov3
python detect.py --images "data/images/dog.jpg, data/images/office.jpg"

# yolov3-tiny
python detect.py --weights ./weights/yolov3-tiny.tf --tiny --images "data/images/dog.jpg"

# webcam
python detect_video.py --video 0

# video file
python detect_video.py --video data/video/paris.mp4 --weights ./weights/yolov3-tiny.tf --tiny

# video file with output saved (can save webcam like this too)
python detect_video.py --video path_to_file.mp4 --output ./detections/output.avi

Then you can find the detections in the detections folder.