Maixpy Dev

MaixPy Development Skill

MaixPy v4 is a Python SDK for edge AI development on Sipeed hardware. This skill provides patterns, examples, and best practices.

Hardware Comparison

| Feature | MaixCAM/MaixCAM-Pro | MaixCAM2 | |---------|---------------------|----------| | CPU | 1GHz RISC-V (Linux) | 1.2GHz A53 x2 (Ubuntu) | | Memory | 256MB DDR3 | 1GB/4GB LPDDR4 | | NPU | 1Tops@INT8 | 3.2Tops@INT8 | | LLM Support | No | Yes (Qwen/DeepSeek) |

Quick Start

from maix import camera, display, image, nn, app

detector = nn.YOLOv8(model="/root/models/yolov8n.mud", dual_buff=True)
cam = camera.Camera(detector.input_width(), detector.input_height(), detector.input_format())
disp = display.Display()

while not app.need_exit():
    img = cam.read()
    objs = detector.detect(img, conf_th=0.5, iou_th=0.45)
    for obj in objs:
        img.draw_rect(obj.x, obj.y, obj.w, obj.h, color=image.COLOR_RED)
        img.draw_string(obj.x, obj.y, f'{detector.labels[obj.class_id]}: {obj.score:.2f}')
    disp.show(img)

Reference Documentation

| Topic | File | Content | |-------|------|---------| | AI Models | [aimodels.md](references/aimodels.md) | YOLO, classifier, face, OCR, pose, segmentation | | Image Processing | [imageprocessing.md](references/imageprocessing.md) | Draw, blobs, edges, QR/barcodes, transforms | | Peripherals | [peripherals.md](references/peripherals.md) | UART, I2C, SPI, GPIO, PWM, ADC | | Network | [network.md](references/network.md) | WiFi, HTTP, MQTT, WebSocket | | Audio | [audio.md](references/audio.md) | Playback, recording, TTS, ASR | | LLM/VLM | [llmvlm.md](references/llmvlm.md) | Qwen, DeepSeek, InternVL (MaixCAM2) | | Tracking | [tracking.md](references/tracking.md) | ByteTracker, counting, trajectories | | Patterns | [patterns.md](references/patterns.md) | Touch UI, threading, state machine, i18n | | Advanced | [advanced.md](references/advanced.md) | OpenCV, video, USB HID, RTSP, protocols |

Device Detection

from maix import sys

device_id = sys.device_id()  # "maixcam", "maixcam2"

if device_id == "maixcam2":
    model = "/root/models/yolo11s.mud"  # Larger model
else:
    model = "/root/models/yolov8n.mud"  # Nano model

Model Paths

Pre-installed models in /root/models/:

• Detection: yolov8n.mud, yolo11n.mud, yolo11s.mud
• Segmentation: yolo11n_seg.mud, yolov8n_seg.mud
• Pose: yolo11n_pose.mud, yolov8n_pose.mud
• Face: yolov8n_face.mud, retinaface.mud
• Classifier: mobilenetv2.mud
• OCR: pp_ocr.mud
• Hand: hand_landmarks.mud

App Development

my_app/
├── app.yaml      # Config (see assets/app.yaml.template)
├── main.py       # Entry point
└── icon.png      # App icon (128x128)

Resources

• Docs: https://wiki.sipeed.com/maixpy/
• API: https://wiki.sipeed.com/maixpy/api/index.html
• GitHub: https://github.com/sipeed/MaixPy
• Examples: https://github.com/sipeed/MaixPy/tree/main/examples
• Projects: https://github.com/sipeed/MaixPy/tree/main/projects
• MaixHub: https://maixhub.com
• Community: QQ群 862340358, t.me/maixpy

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: StanleyChanH
• Source: StanleyChanH/MaixPy-skill
• License: MIT

Install and usage instructions live in the source repository linked above.