def evaluation(loader,
lane_agent,
index=-1,
thresh=p.threshold_point,
name=None):
result_data = deepcopy(loader.test_data)
progressbar = tqdm(range(loader.size_test // 4))
for test_image, target_h, ratio_w, ratio_h, testset_index, gt in loader.Generate_Test(
):
x, y, _ = test(lane_agent, test_image, thresh, index)
x_ = []
y_ = []
for i, j in zip(x, y):
temp_x, temp_y = util.convert_to_original_size(
i, j, ratio_w, ratio_h)
x_.append(temp_x)
y_.append(temp_y)
#x_, y_ = find_target(x_, y_, target_h, ratio_w, ratio_h)
x_, y_ = fitting(x_, y_, target_h, ratio_w, ratio_h)
result_data = write_result_json(result_data, x_, y_, testset_index)
#util.visualize_points_origin_size(x_[0], y_[0], test_image[0], ratio_w, ratio_h)
#print(gt.shape)
#util.visualize_points_origin_size(gt[0], y_[0], test_image[0], ratio_w, ratio_h)
progressbar.update(1)
progressbar.close()
if name == None:
save_result(result_data, "test_result.json")
else:
save_result(result_data, name)
def evaluation(loader, lane_agent, thresh = p.threshold_point, name = None):
result_data = deepcopy(loader.test_data)
for test_image, target_h, ratio_w, ratio_h, testset_index in loader.Generate_Test():
x, y, _ = test(lane_agent, np.array([test_image]), thresh)
x, y = util.convert_to_original_size(x[0], y[0], ratio_w, ratio_h)
x, y = find_target(x, y, target_h, ratio_w, ratio_h)
result_data = write_result_json(result_data, x, y, testset_index)
if name == None:
save_result(result_data, "test_result.json")
else:
save_result(result_data, name)
def evaluation(loader, lane_agent, thresh = p.threshold_point, index= -1, name = None):
progressbar = tqdm(range(loader.size_test//4))
for test_image, ratio_w, ratio_h, path, target_h, target_lanes in loader.Generate_Test():
x, y, _ = test(lane_agent, test_image, thresh, index= index)
x_ = []
y_ = []
for i, j in zip(x, y):
temp_x, temp_y = util.convert_to_original_size(i, j, ratio_w, ratio_h)
x_.append(temp_x)
y_.append(temp_y)
#x_, y_ = find_target(x_, y_, ratio_w, ratio_h)
x_, y_ = fitting(x_, y_, ratio_w, ratio_h)
#util.visualize_points_origin_size(x_[0], y_[0], test_image[0]*255, ratio_w, ratio_h)
#print(target_lanes)
#util.visualize_points_origin_size(target_lanes[0], target_h[0], test_image[0]*255, ratio_w, ratio_h)
result_data = write_result(x_, y_, path)
progressbar.update(1)
progressbar.close()
