What you can do with Lotvulture

4 use cases

• Show live space-by-space occupancy from existing cameras

  Turn existing lot cameras into a live occupancy map with per-space status updates.

  • Lotvulture
  • Work and operations
  • Intermediate
  View prompt

  Using the repo lotvulture/lotvulture, set up Lot Vulture with the Docker command from its README on a Linux host, then add the camera stream <camera_rtsp_url> in the Cameras view. Report the occupancy state of each mapped space shown on the live dashboard at http://localhost:8000, and verify that the states change when a vehicle enters or leaves a mapped space.

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• Push lot availability to road signs and Home Assistant

  Send capacity and space changes over MQTT to LED signage or Home Assistant automations.

  • Lotvulture
  • Work and operations
  • Intermediate
  View prompt

  For the repo lotvulture/lotvulture, configure an MQTT alert in the Lot Vulture dashboard that fires when lot capacity reaches 95 percent, targeting the broker at <mqtt_broker_address> and topic <topic_name>. Report the alert configuration you created and the message payload received, and verify that a test occupancy change produces exactly one message on the topic.

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• Audit past lot use with the scrubbing timeline

  Replay past occupancy by second and open snapshots of each state change.

  • Lotvulture
  • Work and operations
  • Beginner
  View prompt

  For the repo lotvulture/lotvulture running at http://localhost:8000, use the Visual Scrubbing History Timeline to list the occupancy transitions for space <space_name> between <start_time> and <end_time>. Return the transition times and states, and verify that each listed transition has a matching snapshot.

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• Detect parking spaces in one image through the cloud API

  Send one lot photo to the Developer Cloud API and get space detections back.

  • Lotvulture
  • Work and operations
  • Intermediate
  View prompt

  Using the Lot Vulture Developer Cloud API described in the repo lotvulture/lotvulture README, send the image <image_path> with the region coordinates <rois_json> to https://api.lotvulture.com/v1/detect using the API key in the environment variable <api_key_env>. Report the detection result for each region and verify that the number of results equals the number of regions sent.

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How to use Lotvulture

1. Check you have what it needs: One or more IP, RTSP, or snapshot-capable cameras with a reachable stream URL or snapshot endpoint; A Windows PC for the native installer, or a Linux host with Docker for the container; Access to the Releases page or the ghcr.io container image.
2. Open lotvulture/lotvulture on GitHub and read the README and license.
3. Install Lot Vulture: on Windows, run the LotVulture_Setup_*.exe from the Releases page; on Linux, run docker run -d --name lotvulture --restart unless-stopped -p 8000:8000 -v lotvulture-data:/var/lib/lotvulture ghcr.io/lotvulture/lotvulture:latest. (inferred, check the README)
4. Open http://localhost:8000 in a browser.
5. In the Cameras view, add each RTSP stream URL or snapshot endpoint.
6. Use the visual canvas editor to map the four corners of each parking space.

These steps come from our top use case, Show live space-by-space occupancy from existing cameras, which also has a copy-paste agent prompt.

Lotvulture alternatives · Best AI repos for Work and operations

About this repo

• Who it is forParking operators, facilities staff, and developers who already have IP cameras over a lot and want occupancy data without in-ground sensors.
• Why it is hot
• LanguagePython
• Sourcegithub.com/lotvulture/lotvulture · Back to Hot repos

Requirements

• One or more IP, RTSP, or snapshot-capable cameras with a reachable stream URL or snapshot endpoint
• A Windows PC for the native installer, or a Linux host with Docker for the container
• Access to the Releases page or the ghcr.io container image
• A Developer Cloud API key from lotvulture.com, only if using the cloud API use case

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