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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()
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