stable-dreamfusion
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Design of Image-to-3D pipeline
The image to 3d demo results look surprisingly good! May I ask if there are detailed documentation that illustrates how it works?
I also want to learn about more details about Image-to-3D generation!
I finetune Zero123 with some images and get the improvement on novel view synthesis. However, the results are quite similar to the original zero123 ckpt when I run with the finetuned ckpt.
The commmand I use is:
# Init
CUDA_VISIBLE_DEVICES=${{GPU_ID}} python main.py -O \
--image path_to_img_raba \
--workspace logs/init \
--iters 5000 \
--batch_size 2 \
--h 96 --w 96 \
--guidance_scale 5 \
--eval_interval 50 \
--zero123_ckpt path_to_finetuned_ckpt \
--zero123_config path_to_my_yaml
# Finetune
CUDA_VISIBLE_DEVICES=${{GPU_ID}} python main.py -O \
--image path_to_img_raba \
--workspace logs/refine \
--iters 10000 \
--batch_size 2 \
--guidance_scale 5 \
--h 96 --w 96 \
--eval_interval 50 \
--dmtet --init_with path_to_init_ckpt
This repo is sooooooo AWESOME! Could you please share more detailed documentations about 2D-to-3D generation with only Zero123 guidance?