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Running
on
Zero
Running
on
Zero
import os | |
import numpy as np | |
from tqdm import tqdm | |
# ours + NeuS | |
DATA_DIR = "/home/xin/data/EscherNet/Data/GSO30" # GSO | |
exp_dir = "/home/xin/6DoF/GSO3D/" | |
config = "configs/neus_36.yaml" | |
exps = [1] | |
# exps = [1, 2, 3, 5, 10] | |
for exp in exps: | |
OUTPUT_DIR = os.path.join(exp_dir, f"logs_GSO_T{exp}M36_99k") | |
output_NeuS = f"ours_GSO_T{exp}" | |
os.makedirs(output_NeuS, exist_ok=True) | |
obj_names = os.listdir(DATA_DIR) | |
for obj_name in tqdm(obj_names): | |
if os.path.exists(os.path.join(output_NeuS, "NeuS", obj_name, "mesh.ply")): | |
print("NeuS already trained for: ", obj_name) | |
continue | |
# remove the folder for new training | |
os.system(f"rm -rf {output_NeuS}/NeuS/{obj_name}") | |
print("Training NeuS for: ", obj_name) | |
input_img = os.path.join(OUTPUT_DIR, obj_name, "0.png") | |
# input_img = os.path.join(OUTPUT_DIR, obj_name, "gt.png") # ground truth image | |
cmd = f"python train_renderer.py -i {input_img} \ | |
-d {DATA_DIR} \ | |
-n {obj_name} \ | |
-b {config} \ | |
-l {output_NeuS}/NeuS" | |
os.system(cmd) |