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- Closes #3: execute_pick and execute_lift now accept an optional current_pos parameter. Callers (execute_command) pass self.current_pos so move_line starts from the actual arm position rather than a hardcoded [120, 0, 60] default. Falls back to rest position when None. - Closes #4: add requirements.txt with correct package names. Note: README listed 'openai-whisper' but the code imports faster_whisper; requirements.txt uses the correct 'faster-whisper' package name. - Replace all `servo_buffer = []` assignments with `.clear()` to stay compatible with the deque introduced in PR #8 (#6 follow-up). - Partial #5: translate Chinese print/comment strings to English in execute_pick, execute_lift, and execute_command.
33 lines
898 B
Text
33 lines
898 B
Text
# Robot Arm Voice Control System - Dependencies
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# Python 3.10+ required
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#
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# GPU acceleration (CUDA 11.8 / 12.x) is strongly recommended.
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# Install PyTorch with CUDA from: https://pytorch.org/get-started/locally/
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# Example (CUDA 12.1):
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# pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
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# --- Core scientific stack ---
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numpy>=1.24
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scipy>=1.11
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# --- Serial communication ---
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pyserial>=3.5
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# --- Computer vision ---
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opencv-python>=4.8
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ultralytics>=8.0 # YOLOv8
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# --- Audio ---
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sounddevice>=0.4.6
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# --- Speech recognition ---
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faster-whisper>=1.0.0 # NOTE: this is faster-whisper, NOT openai-whisper
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# --- LLM inference ---
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torch>=2.0 # install with CUDA wheels from pytorch.org
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transformers>=4.40
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accelerate>=0.27
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peft>=0.10 # LoRA adapter loading
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# --- Visualization (arm_main.py demo) ---
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matplotlib>=3.7
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