| import tqdm | |
| import imageio | |
| import json | |
| import os.path as osp | |
| import os | |
| from oee.utils import plt_utils | |
| from oee.utils.elev_est_api import elev_est_api | |
| def visualize(img_paths, elev): | |
| imgs = [imageio.imread_v2(img_path) for img_path in img_paths] | |
| plt_utils.image_grid(imgs, 2, 2, label=f"elev={elev}") | |
| def estimate_elev(root_dir): | |
| # root_dir = "/home/linghao/Datasets/objaverse-processed/zero12345_img/wild" | |
| # dataset = "supp_fail" | |
| # root_dir = "/home/chao/chao/OpenComplete/zero123/zero123/gradio_tmp/" | |
| # obj_names = sorted(os.listdir(root_dir)) | |
| # results = {} | |
| # for obj_name in tqdm.tqdm(obj_names): | |
| img_dir = osp.join(root_dir, "stage2_8") | |
| img_paths = [] | |
| for i in range(4): | |
| img_paths.append(f"{img_dir}/0_{i}.png") | |
| elev = elev_est_api(img_paths) | |
| # visualize(img_paths, elev) | |
| # results[obj_name] = elev | |
| # json.dump(results, open(osp.join(root_dir, f"../{dataset}_elev.json"), "w"), indent=4) | |
| return elev | |
| # if __name__ == '__main__': | |
| # main() | |