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export CUDA=0
export BASE_TEST_DATA_DIR="datasets/eval/"
export CHECKPOINT_DIR="jingheya/lotus-normal-g-v1-1"
export OUTPUT_DIR="output/Normal_G_Eval"
export TASK_NAME="normal"
export MODE="generation"
CUDA_VISIBLE_DEVICES=$CUDA python eval.py \
--pretrained_model_name_or_path=$CHECKPOINT_DIR \
--prediction_type="sample" \
--seed=42 \
--half_precision \
--base_test_data_dir=$BASE_TEST_DATA_DIR \
--task_name=$TASK_NAME \
--mode=$MODE \
--output_dir=$OUTPUT_DIR \
--disparity
# You can set `processing_res` for high-resolution images. Default: `--processing_res=None`.
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