Pole-detection-using-darknet

A system that can rocognize a pole in a image or video given and react according to it. It uses a “convolutional neural network” achitecture to detect and classify objects on the image. It require a set of data consisting of images of poles from various angles. The images are then labeled using a tool which draws a rectangle around the image where the pole is located. These labeled images are resized and proccessed to reduce its size before training the neural network. The neural network is trained on these images and can succssfully detect poles on a image or video.

Training Chart (graph)

Prediction

Terminal command for testing

for Video:

./darknet detector demo cfg/trainer.data cfg/obj-yolov3-tiny.cfg obj-yolov3-tiny_6000.weights "video.mp4"

for Image:

./darknet detector test cfg/trainer.data cfg/obj-yolov3-tiny.cfg obj-yolov3-tiny_6000.weights "image.jpg"