DetectorPlacas is a computer vision project built with TensorFlow and OpenCV that automatically detects vehicle license plates in real time. It ships with a pre-trained frozen inference graph based on SSD MobileNet v1 and supports three detection modes — static images, video files, and live webcam streams — all accessible through a Tkinter graphical interface or directly from the command line.Documentation Index
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Introduction
Understand how DetectorPlacas works and explore the detection pipeline architecture.
Quickstart
Install dependencies and run your first license plate detection in minutes.
Detection Modes
Run detection on images, video files, or a live webcam feed with configurable thresholds.
Script Reference
Full reference for all Python scripts, flags, constants, and tensor names.
How it works
Install dependencies
Set up Python, TensorFlow 1.15, OpenCV, NumPy, and the TensorFlow Object Detection API.
Prepare model artifacts
Place the frozen inference graph (
frozen_inference_graph.pb) and labelmap.pbtxt in the expected directory layout.Choose a detection mode
Launch the Tkinter GUI (
interfaz.py) or call an individual detection script directly from the terminal.