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What you can do with JEV Sees

JEV Sees is an open-source Python project that detects objects in images, video, and RGB-D camera feeds, tracks them across frames, and asks the JEV model a question about each one.

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CharlesFeng0314/JEV_sees on GitHub

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What do you want to do?

5 use cases

  • Ask JEV a color question about each object in a photo

    Detect objects in one image and get a per-object color answer from a fixed list of options.

    View prompt
    In the JEV_sees repo at <repo path>, with TYPESAFE_API_KEY set, run examples/bus_color.py and report the printed rows for assets/bus.jpg. Expect a table with object_id, label, choice, and confidence columns; verify that each choice is one of the listed colors.

  • Score each tracked pedestrian's accident probability in a clip

    Get a per-frame probability for every tracked pedestrian in a short traffic video segment.

    View prompt
    In the JEV_sees repo at <repo path>, with TYPESAFE_API_KEY set, run examples/traffic_relations.py on assets/traffic.mp4 for frames 504 to 600. Report frame_index, object_id, and probability for each pedestrian; verify that the output describes the current frame and does not forecast future accidents.

  • Label each tracked animal's motion state in a video

    Assign stationary, walking, running, or uncertain to every tracked animal in a clip.

    View prompt
    In the JEV_sees repo at <repo path>, with TYPESAFE_API_KEY set, run examples/animal_motion.py on assets/black_cat_walking.mp4. Report frame_index, video_time_s, object_id, and choice for the output; verify that every choice is one of stationary, walking, running, or uncertain.

  • Grade how obstructed each package is in a photo

    Score every detected package in a warehouse image against a rubric you define.

    View prompt
    In the JEV_sees repo at <repo path>, write and run a Python script that calls Sees().for_each("package").score(...) on <photo path> with the rubric 0: clear, 1: partly obstructed, 2: heavily obstructed. Expect one score per package in output.json; verify that every score is one of the three rubric levels.

  • Ask JEV questions about objects from a live RGB-D camera

    Feed RGB and depth frames into a loop and ask JEV about detected objects with 3D positions.

    View prompt
    In the JEV_sees repo at <repo path>, write a camera loop that calls observe(rgb, depth, intrinsics=...) on each frame from <camera source> and then ask(...) with the question What is this object? Expect printed JEV answers per object; verify that objects include 3D positions or distances when intrinsics are supplied.

How to use JEV Sees

  1. Check you have what it needs: Python 3.10 or newer; A JEV API key from console.typesafe.ai/keys; Internet access for the first run, unless the Florence-2 and CLIP weights are already available locally.
  2. Open CharlesFeng0314/JEV_sees on GitHub and read the README and license.
  3. Clone the project with git clone https://github.com/CharlesFeng0314/JEV_sees.git.
  4. Enter the folder with cd JEV_sees.
  5. Install it with python -m pip install -e ..
  6. Set your key on macOS or Linux with export TYPESAFE_API_KEY="your-key", or in PowerShell with $env:TYPESAFE_API_KEY = "your-key".

These steps come from our top use case, Ask JEV a color question about each object in a photo, which also has a copy-paste agent prompt.

JEV Sees alternatives · Best AI repos for Research

About this repo

Requirements

  • Python 3.10 or newer
  • A JEV API key from console.typesafe.ai/keys
  • Internet access for the first run, unless the Florence-2 and CLIP weights are already available locally
  • Git and a terminal
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Questions about JEV Sees

What is JEV Sees?

JEV Sees is an open-source Python project that detects objects in images, video, and RGB-D camera feeds, tracks them across frames, and asks the JEV model a question about each one. It is an open-source project on GitHub: https://github.com/CharlesFeng0314/JEV_sees.

Who is JEV Sees for?

Built for Python developers and AI agents who want per-object visual answers from photos, clips, or live camera streams, and who have a JEV API key.

What can I do with JEV Sees?

5 use cases so far, for example: Ask JEV a color question about each object in a photo; Score each tracked pedestrian's accident probability in a clip; Label each tracked animal's motion state in a video. Each has steps and a copy-paste agent prompt.

What do I need to run JEV Sees?

Python 3.10 or newer; A JEV API key from console.typesafe.ai/keys; Internet access for the first run, unless the Florence-2 and CLIP weights are already available locally; Git and a terminal.

What are alternatives to JEV Sees?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is JEV Sees safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.