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84 lines
2.7 KiB
Bash
Executable File
84 lines
2.7 KiB
Bash
Executable File
#!/bin/bash
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# Example script to run subtask annotation with Qwen VLM.
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# Generates skill/subtask segments for hierarchical policy training.
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#
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# Usage:
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# ./scripts/run_subtask_annotate.sh
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# Or with env overrides:
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# REPO_ID=user/other-dataset OUTPUT_DIR=/tmp/out ./scripts/run_subtask_annotate.sh
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set -e
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# --------------- Configuration ---------------
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REPO_ID="${REPO_ID:-lerobot-data-collection/round1_4}"
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# MODEL="${MODEL:-Qwen/Qwen3-VL-30B-A3B-Thinking}"
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MODEL="${MODEL:-Qwen/Qwen3.5-27B}"
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# Or: MODEL="Qwen/Qwen2-VL-7B-Instruct"
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OUTPUT_DIR="${OUTPUT_DIR:-/fsx/jade_choghari/outputs/collect-data-pgen_new}"
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BATCH_SIZE="${BATCH_SIZE:-4}"
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VIDEO_KEY="${VIDEO_KEY:-observation.images.base}"
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# Closed-vocabulary subtask labels (optional). Pass as space-separated list.
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# Leave empty for open-vocabulary segmentation.
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SUBTASK_LABELS=(
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"do_first_horizontal_fold"
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"do_second_horizontal_fold"
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"do_third_fold_left_to_right"
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"do_fourth_fold_right_to_left"
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"rotate_t-shirt_90_degrees"
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"slide_folded_shirt_to_right"
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)
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# --------------- Run subtask annotation ---------------
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# Uses the refactored CLI: lerobot-dataset-subtask-annotate (config-based, snake_case args).
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# If not installed, run from repo root: PYTHONPATH=src python -m lerobot.scripts.lerobot_subtask_annotate ...
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CMD=(
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lerobot-dataset-subtask-annotate
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--repo_id "$REPO_ID"
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--video_key "$VIDEO_KEY"
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--output_dir "$OUTPUT_DIR"
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--push_to_hub True
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--no_timer_overlay True
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--model "$MODEL"
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--batch_size "$BATCH_SIZE"
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)
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# Add closed-vocabulary labels if defined
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if [ ${#SUBTASK_LABELS[@]} -gt 0 ]; then
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for label in "${SUBTASK_LABELS[@]}"; do
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CMD+=(--subtask_labels "$label")
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done
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fi
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echo "Running: ${CMD[*]}"
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"${CMD[@]}"
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# --------------- Optional: image-window annotator (if available) ---------------
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# Uncomment and adjust path if you use the image-window variant:
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# python /path/to/lerobot/data_processing/annotations/subtask_annotate_image.py \
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# --repo-id "$REPO_ID" \
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# --camera-key observation.images.wrist \
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# --output-dir "$OUTPUT_DIR" \
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# --output-repo-id "jadechoghari/piper-demo-annotated1-image" \
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# --push-to-hub \
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# --model "$MODEL" \
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# --window-size 184 \
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# --max-frames-per-window 16 \
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# --subtask-labels "label1" "label2" \
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# --batch-size 2
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# --------------- Optional: synthetic data generation (pgen) ---------------
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# BATCH_SIZE=2 TEMPERATURE=0.9 SAMPLE_INTERVAL=5.0
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# python examples/dataset/annotate_pgen.py \
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# --repo-id "$REPO_ID" \
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# --model "$MODEL" \
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# --output-dir "$OUTPUT_DIR" \
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# --temperature "$TEMPERATURE" \
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# --batch-size "$BATCH_SIZE" \
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# --sample-interval "$SAMPLE_INTERVAL" \
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# --image-key observation.images.base \
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# --num-image-views-per-sample 1
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# Add --push-to-hub to push after generation.
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