pranjalAI

import tensorflow as tf
physical_devices = tf.config.experimental.list_physical_devices('GPU')
if len(physical_devices) > 0:
    tf.config.experimental.set_memory_growth(physical_devices[0], True)
from absl import app, flags, logging
from absl.flags import FLAGS
import core.utils as utils
from core.yolov4 import filter_boxes
from tensorflow.python.saved_model import tag_constants
from PIL import Image

pranjalAI

from __future__ import division, print_function
# coding=utf-8
import sys
import os
import glob
import re, glob, os,cv2
import numpy as np
import pandas as pd
import detect_object
from shutil import copyfile

pranjalAI

import os, random, shutil
import numpy as np
import pandas as pd
import PIL
#import keras
import itertools
from PIL import Image

import tensorflow as tf

pranjalAI

datagen = ImageDataGenerator(rescale=1.0/255.0)

train_path = 'Your Image Folder Path'
train_batches = datagen.flow_from_directory(train_path, target_size=(200,200), classes=classes_required, batch_size=batch_size_train)

pranjalAI

model=Sequential()
model.add(Conv2D(16,kernel_size=(3,3), activation="relu" ,input_shape=IMAGE_SIZE + [3], padding='same'))

model.add(Conv2D(32, kernel_size=(3,3), activation="relu",padding='same'))
model.add(BatchNormalization()) 
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Dropout(0.30))

model.add(Conv2D(64, kernel_size=(3,3), activation="relu",padding='same'))
#model.add(BatchNormalization()) 

pranjalAI

test_image=cv2.imread("IMAGE_PATH")
test_image = np.expand_dims(test_image, axis=0)
out=np.argmax(model_loaded.predict(test_image))
Ans=np.where(out==0, "Middle",
         (np.where(out==1,"Old",
         "Young"))).item()
print(Ans+" age person.")

pranjalAI

from google.colab import drive
drive.mount('/content/gdrive')
!ln -s /content/gdrive/My\ Drive/ /mydrive
!ls /mydrive

pranjalAI

!git clone https://github.com/AlexeyAB/darknet
# verify CUDA
!/usr/local/cuda/bin/nvcc --version

# change makefile to have GPU and OPENCV enabled
%cd darknet
!sed -i 's/OPENCV=0/OPENCV=1/' Makefile
!sed -i 's/GPU=0/GPU=1/' Makefile
!sed -i 's/CUDNN=0/CUDNN=1/' Makefile
!sed -i 's/CUDNN_HALF=0/CUDNN_HALF=1/' Makefile

pranjalAI

!sed -i 's/batch=1/batch=64/' cfg/yolov4.cfg
!sed -i 's/subdivisions=1/subdivisions=16/' cfg/yolov4.cfg
!sed -i 's/max_batches = 500500/max_batches = 6000/' cfg/yolov4.cfg     
!sed -i '968 s@classes=80@classes=1@' cfg/yolov4.cfg                  
!sed -i '1056 s@classes=80@classes=1@' cfg/yolov4.cfg
!sed -i '1144 s@classes=80@classes=1@' cfg/yolov4.cfg
!sed -i '961 s@filters=255@filters=18@' cfg/yolov4.cfg        .
!sed -i '1049 s@filters=255@filters=18@' cfg/yolov4.cfg
!sed -i '1137 s@filters=255@filters=18@' cfg/yolov4.cfg

pranjalAI

!echo "Glasses" > data/obj.names
!echo -e 'classes= 1\ntrain  = data/train.txt\nvalid  = data/test.txt\nnames = data/obj.names\nbackup = /mydrive/yolov4_v1' > data/obj.data
!mkdir data/obj