detector_codes/LGrad-master/CNNDetection/validate.py

import torch
import numpy as np
from sklearn.metrics import average_precision_score, accuracy_score
from options.test_options import TestOptions
from data import create_dataloader


def validate(model, val_loader):
    # data_loader = create_dataloader(opt)

    with torch.no_grad():
        y_true, y_pred = [], []
        for img, label in val_loader:
            in_tens = img.cuda()
            y_pred.extend(model(in_tens).sigmoid().flatten().tolist())
            y_true.extend(label.flatten().tolist())

    y_true, y_pred = np.array(y_true), np.array(y_pred)
    r_acc = accuracy_score(y_true[y_true==0], y_pred[y_true==0] > 0.5)
    f_acc = accuracy_score(y_true[y_true==1], y_pred[y_true==1] > 0.5)
    acc = accuracy_score(y_true, y_pred > 0.5)
    ap = average_precision_score(y_true, y_pred)
    return acc, ap, r_acc, f_acc