Image Classification Model Built on a subset of CIFAR-10 Dataset for Classification of various images.
The Sequential Model takes an image with input Size (32,32,3) and produces a output vector with 3 classes.
1.Aeroplane
2.Car
3.Bird
To Use:
1.Download the GIT repository as Zip and Extract.
2.Run pip install requirements.txt
2.5.Change the working directory Command in server.py "os.chdir(r"C:\Users\LENOVO\Desktop\sample_project_1\Take It Out")" to os.chdir({YOUR WORKING DIRECTORY}) .
3.Run server.py on Terminal.
4.Open http://127.0.0.1:5000/index
Information about the custom model:
Model architecture:
conv2d (Conv2D) (None, 32, 32, 32) 896
batch_normalization (BatchNo (None, 32, 32, 32) 128
conv2d_1 (Conv2D) (None, 30, 30, 32) 9248
max_pooling2d (MaxPooling2D) (None, 15, 15, 32) 0
dropout (Dropout) (None, 15, 15, 32) 0
conv2d_2 (Conv2D) (None, 15, 15, 64) 18496
batch_normalization_1 (Batch (None, 15, 15, 64) 256
conv2d_3 (Conv2D) (None, 13, 13, 64) 36928
max_pooling2d_1 (MaxPooling2 (None, 6, 6, 64) 0
dropout_1 (Dropout) (None, 6, 6, 64) 0
conv2d_4 (Conv2D) (None, 6, 6, 128) 73856
batch_normalization_2 (Batch (None, 6, 6, 128) 512
conv2d_5 (Conv2D) (None, 4, 4, 128) 147584
max_pooling2d_2 (MaxPooling2 (None, 2, 2, 128) 0
dropout_2 (Dropout) (None, 2, 2, 128) 0
flatten (Flatten) (None, 512) 0
Output Layer