sridevibonthu/YoloV3

YoloV3

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YoloV3 Simplified for training on Colab with custom dataset for one class (GUN)

A Collage of Training images

A Collage of Testing images

Class - gun

1. We have added a 500 images of unique object (gun) in the folder customdata after annotating the images using Annotation Tool. The structure we followed to store them is

data
  --customdata
    --images/
      --img001.jpg
      --img002.jpg
      --...
    --labels/
      --img001.txt
      --img002.txt
      --...
    custom.data #data file
    custom.names #class name
    customtrain.txt #list of name of the images to train our network.
    customtest.txt #list of names of the images for validation

2. For one class example our custom.data is here. We used 500 images for training and 100 images for testng.
3. downloaded the weights (yolov3-spp-ultralytics.pt) from the original and placed in Google Drive.
4. Created a weights folder under YoloV3 to store weights
5. Trained for 300 epochs after configuring. (log)[https://github.com/sridevibonthu/YoloV3/blob/master/results.txt)

Results

After training for 300 Epochs, results look awesome!

Performance