tf-explain-visualize2.py

from argparse import ArgumentParser
from os import path

import numpy as np
import tf_explain
from cv2 import imread, cvtColor, resize, COLOR_BGR2RGB
from tensorflow.keras.models import load_model

from utils.constants import CLASSES, IMG_DIMENSIONS

parser = ArgumentParser()
parser.add_argument("model", help=f"specify model ")
parser.add_argument("-c", "--classindex",default=0,type=int)
parser.add_argument('-d', '--dataset',default="dataset")
args = vars(parser.parse_args())
data = []

from os import listdir
from os.path import isfile, join
mypath = args['dataset']
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
for f in onlyfiles:
    print(f)
    image = imread(path.join(args['dataset'], f))
    image = cvtColor(image, COLOR_BGR2RGB)
    image = resize(image, IMG_DIMENSIONS)
    data.append(image)

data = np.array(data) / 255.0
explainer = tf_explain.core.grad_cam.GradCAM()
data = (data, None)
model = load_model(args['model'])

for layer in model.layers:
    if "conv" in layer.name.lower():
        gradcam_layer=layer.name

# Start explainer
grid = explainer.explain(data, model, class_index=args['classindex'], layer_name=gradcam_layer)  #
from datetime import datetime
now = datetime.now()
current_time = now.strftime("%H_%M_%S")
saveloc = mypath
filename = f"{current_time}_class_{CLASSES[args['classindex']]}"
filename += ".jpg"
try:
    explainer.save(grid,f"{saveloc}", f"{filename}")
    print(f"GradCam image created and saved to {saveloc}/{filename}")
except:
    print("F")