{"id":13802472,"url":"https://github.com/Dnapert/LidarLight_v3HP_micropython","last_synced_at":"2025-05-13T13:31:21.996Z","repository":{"id":219807749,"uuid":"749986298","full_name":"Dnapert/LidarLight_v3HP_micropython","owner":"Dnapert","description":"A micropython library for the garmin lidar light v3hp","archived":false,"fork":false,"pushed_at":"2024-01-30T00:13:13.000Z","size":14,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-08-04T00:07:15.295Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Dnapert.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-01-29T19:18:55.000Z","updated_at":"2024-08-04T00:07:17.510Z","dependencies_parsed_at":"2024-01-29T22:24:33.750Z","dependency_job_id":"f35ca087-2a15-4551-8ba8-be8930fa5832","html_url":"https://github.com/Dnapert/LidarLight_v3HP_micropython","commit_stats":null,"previous_names":["dnapert/lidarlight_v3hp_micropython"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Dnapert%2FLidarLight_v3HP_micropython","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Dnapert%2FLidarLight_v3HP_micropython/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Dnapert%2FLidarLight_v3HP_micropython/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Dnapert%2FLidarLight_v3HP_micropython/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Dnapert","download_url":"https://codeload.github.com/Dnapert/LidarLight_v3HP_micropython/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225218075,"owners_count":17439713,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-04T00:01:45.175Z","updated_at":"2024-11-18T17:31:27.939Z","avatar_url":"https://github.com/Dnapert.png","language":"Python","funding_links":[],"categories":["Libraries"],"sub_categories":["Sensors"],"readme":"# MicroPython library for the Garmin Lidar Lite v3HP\n\n## This is a basic MicroPython library for the Garmin Lidar Lite v3HP. It is based on the official [Arduino library ](https://github.com/garmin/LIDARLite_Arduino_Library/blob/master/src/LIDARLite_v3HP.cpp) and the official [Datasheet](https://static.garmin.com/pumac/LIDAR-Lite_v3HP_Instructions_EN.pdf).\n\n\nBasic usage:\n\n```python\nfrom machine import I2C, Pin\nfrom lidarLitev3hp import V3HP\n\ni2c = I2C(1, scl=Pin(7), sda=Pin(6), freq=400000)\n# Class is initialized with the mode, and the i2c object\nlidar = V3HP( 0 ,   i2c)\n\n# Single measurement, most accurate\ndistance = lidar.range()\n\n# Single measurement, fast method, potentially less accurate\ndistance = lidar.range_fast()\n```\n\n## Modes\n\n    0: Default mode, balanced performance.\n\n    1: Short range, high speed.\n\n    2: Default range, higher speed short range. Turns on quick termination detection for faster measurements at short range (with decreasedaccuracy)\n\n    3: Maximum range.\n\n    4: High sensitivity detection. Overrides default valid measurement detection algorithm, and uses a threshold value for high sensitivity and noise.\n\n    5: Low sensitivity detection. Overrides default valid measurement detection algorithm, and uses a threshold value for low sensitivity and noise.\n\n    6: Short range, high speed, higher error. Overrides default valid measurement\n\n### On the pi pico, I was able to get a reliable 330 measurements per second using mode 1 with range_fast method, and 280 measurements per second using mode 1 with the standard range method.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDnapert%2FLidarLight_v3HP_micropython","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FDnapert%2FLidarLight_v3HP_micropython","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDnapert%2FLidarLight_v3HP_micropython/lists"}