task07/model.py - master - sat1988/MachineVision

task07/model.py
52 строки2 KB
Oleg Chorakaev
Добавлен 7 пример
26 июл 2025, 16:13
26 июл 2025, 16:130a00484
from tensorflow.keras import layers as L
from tensorflow.keras.models import Model
from tensorflow.keras.applications import MobileNetV2
from tensorflow.python.keras import Sequential
from tensorflow.python.layers.pooling import MaxPooling2D
from keras.layers import Conv2D
from keras.layers import Dropout
from keras.layers import Flatten
from keras.layers import Dense
from tensorflow_datasets.image_classification.colorectal_histology_test import num_classes
from tensorflow_hub.keras_layer import keras

def build_model(input_shape):
    """ Inputs """
    inputs = L.Input(input_shape)

    """ Backbone """
    backbone = MobileNetV2(
        include_top=False,
        weights="imagenet",
        input_tensor=inputs,
        alpha=1.0
    )
    backbone.trainable = False
    # backbone.summary()

    """ Detection Head """
    #x = backbone.output
    #x = L.Conv2D(256, kernel_size=1, padding="same")(x)
    #x = L.BatchNormalization()(x)
    #x = L.Activation("relu")(x)
    #x = L.GlobalAveragePooling2D()(x)
    #x = L.Dropout(0.5)(x)
    #x = L.Dense(4, activation="sigmoid")(x)

    """ Model """
    #model = Model(inputs, x)

    model = Sequential()
    model.add(Conv2D(32, kernel_size = (3, 3), activatoin = 'relu', input_shape = input_shape))
    model.add(MaxPooling2D(pool_size = (2, 2)))
    model.add(Conv2D(64, kernel_size=(3, 3), activatoin='relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Conv2D(64, kernel_size=(3, 3), activatoin='relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Dropout(0.25))
    model.add(Flatten())
    model.add(Dense(128, activation = 'relu'))
    model.add(Dropout(0.5))
    model.add(Dense(num_classes, activation='softmax'))
    model.compile(loss=keras.losses.categorical_crossentropy, optimizer = keras.optimizer.Adadelta(), metrics=['accuracy'])
    return model