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import os
import cv2
import argparse
import numpy as np
import torch
import torchvision
from torchvision import datasets, transforms
from torch.autograd import Variable
from network_v0.model import PointModel
from datasets.hp_loader import PatchesDataset
from torch.utils.data import DataLoader
from evaluation.evaluate import evaluate_keypoint_net
def main():
parser = argparse.ArgumentParser(description='Testing')
parser.add_argument('--device', default=0, type=int, help='which gpu to run on.')
parser.add_argument('--test_dir', required=True, type=str, help='Test data path.')
opt = parser.parse_args()
torch.manual_seed(0)
use_gpu = torch.cuda.is_available()
if use_gpu:
torch.cuda.set_device(opt.device)
# Load data in 320x240
hp_dataset_320x240 = PatchesDataset(root_dir=opt.test_dir, use_color=True, output_shape=(320, 240), type='all')
data_loader_320x240 = DataLoader(hp_dataset_320x240,
batch_size=1,
pin_memory=False,
shuffle=False,
num_workers=4,
worker_init_fn=None,
sampler=None)
# Load data in 640x480
hp_dataset_640x480 = PatchesDataset(root_dir=opt.test_dir, use_color=True, output_shape=(640, 480), type='all')
data_loader_640x480 = DataLoader(hp_dataset_640x480,
batch_size=1,
pin_memory=False,
shuffle=False,
num_workers=4,
worker_init_fn=None,
sampler=None)
# Load model
model = PointModel(is_test=True)
ckpt = torch.load('./checkpoints/PointModel_v0.pth')
model.load_state_dict(ckpt['model_state'])
model = model.eval()
if use_gpu:
model = model.cuda()
print('Evaluating in 320x240, 300 points')
rep, loc, c1, c3, c5, mscore = evaluate_keypoint_net(
data_loader_320x240,
model,
output_shape=(320, 240),
top_k=300)
print('Repeatability: {0:.3f}'.format(rep))
print('Localization Error: {0:.3f}'.format(loc))
print('H-1 Accuracy: {:.3f}'.format(c1))
print('H-3 Accuracy: {:.3f}'.format(c3))
print('H-5 Accuracy: {:.3f}'.format(c5))
print('Matching Score: {:.3f}'.format(mscore))
print('\n')
print('Evaluating in 640x480, 1000 points')
rep, loc, c1, c3, c5, mscore = evaluate_keypoint_net(
data_loader_640x480,
model,
output_shape=(640, 480),
top_k=1000)
print('Repeatability: {0:.3f}'.format(rep))
print('Localization Error: {0:.3f}'.format(loc))
print('H-1 Accuracy: {:.3f}'.format(c1))
print('H-3 Accuracy: {:.3f}'.format(c3))
print('H-5 Accuracy: {:.3f}'.format(c5))
print('Matching Score: {:.3f}'.format(mscore))
print('\n')
if __name__ == '__main__':
main()
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