Skip to main content

Add your description here

Project description

VLM-RECog

A Python library for zero-shot object detection and segmentation using Vision-Language Models (VLMs), built on Google's Gemini 2.5 Flash model.

Installation

pip install vlm-recog
export GEMINI_API_KEY=<your_api_key>

Requirements

  • Python 3.11+
  • Google Gemini API key (set as GEMINI_API_KEY environment variable)

Quick Start

from PIL import Image
from vlm_recog.detection import detect
from vlm_recog.visualization import draw_detections

# Load an image
image = Image.open("path/to/image.jpg")

# Detect objects by text labels
result = detect(image, ["dog", "bicycle", "person"])

# Visualize results
output_image = draw_detections(image, result)
output_image.show()

Demo

output

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

vlm_recog-0.1.9.tar.gz (1.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

vlm_recog-0.1.9-py3-none-any.whl (7.1 kB view details)

Uploaded Python 3

File details

Details for the file vlm_recog-0.1.9.tar.gz.

File metadata

  • Download URL: vlm_recog-0.1.9.tar.gz
  • Upload date:
  • Size: 1.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.5.13

File hashes

Hashes for vlm_recog-0.1.9.tar.gz
Algorithm Hash digest
SHA256 d412bab2931218c0baf818986e98c7fc6e6947df2832cb3a2b43d5e7a4a67904
MD5 2bc3d0c237438f047354adbb8f27e6f9
BLAKE2b-256 d0db4aeae3aa30dbb107c6b2cfaf731226a0df0021803896caa6ddc2aca56886

See more details on using hashes here.

File details

Details for the file vlm_recog-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: vlm_recog-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 7.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.5.13

File hashes

Hashes for vlm_recog-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 e61050c831ec8fa4c48f31050f982686c567aefeabff910d4792d0dd9d110272
MD5 5aaf4aa1493f542a3ec4601411987ac7
BLAKE2b-256 a267ff772d8d3bf186c7978698cd460e04cf649ef8f2e4d27137d251608d6304

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page