Praveen76

Praveen76

Praveen76

import os
print(os.getcwd())

git clone https://github.com/fizyr/keras-retinanet.git
%cd keras-retinanet/

!pip install .
!python setup.py build_ext --inplace

Praveen76

import os
print(os.getcwd())

git clone https://github.com/fizyr/keras-retinanet.git
%cd keras-retinanet/

!pip install .
!python setup.py build_ext --inplace

Praveen76

import numpy as np
import shutil
import pandas as pd
import os, sys, random
import xml.etree.ElementTree as ET
import pandas as pd
from os import listdir
from os.path import isfile, join
import matplotlib.pyplot as plt
from PIL import Image

Praveen76

pngPath='C:/Users/PraveenKumar/RetinaNet//maskDetectorJPEGImages/'
annotPath='C:/Users/PraveenKumar/RetinaNet//maskDetectorXMLfiles/'

data=pd.DataFrame(columns=['fileName','xmin','ymin','xmax','ymax','class'])

os.getcwd()
#read All files
allfiles = [f for f in listdir(annotPath) if isfile(join(annotPath, f))]

#Read all pdf files in images and then in text and store that in temp folder 

Praveen76

# pick a random image
  filepath = df.sample()['fileName'].values[0]

  # get all rows for this image
  df2 = df[df['fileName'] == filepath]
  im = np.array(Image.open(filepath))

  # if there's a PNG it will have alpha channel
  im = im[:,:,:3]

Praveen76

#Define labels & write them in a file
classes = ['mask','noMask']
with open('../maskDetectorClasses.csv', 'w') as f:
  for i, class_name in enumerate(classes):
    f.write(f'{class_name},{i}\n')
            
if not os.path.exists('snapshots'):
  os.mkdir('snapshots')

Praveen76

URL_MODEL = 'https://github.com/fizyr/keras-retinanet/releases/download/0.5.1/resnet50_coco_best_v2.1.0.h5'
urllib.request.urlretrieve(URL_MODEL, PRETRAINED_MODEL)

Praveen76

#Put your training data path & file that has labels for your training data 
!keras_retinanet/bin/train.py 
        --freeze-backbone
        --random-transform
        --weights {PRETRAINED_MODEL}
        --batch-size 8
        --steps 500
        --epochs 15
        csv maskDetectorData.csv 
        maskDetectorClasses.csv