This repository is an implementation of parking slot detection in AVM (around view images) using deep learning. The implementation is based on following References.
around view image
- Research Review on Parking Space Detection Method
- Vacant Parking Slot Detection in the Around View Image Based on Deep Learning
- Parking Slot Detection on Around-View Images Using DCNN
- Vision-Based Parking-Slot Detection: A DCNN-Based Approach and a Large-Scale Benchmark Dataset
- Real Time Detection Algorithm of Parking Slot Based on Deep Learning and Fisheye Image
- A Deep-Learning Approach for Parking Slot Detection on Surround-View Images
- Context-Based Parking Slot Detection With a Realistic Dataset
- End to End Trainable One Stage Parking Slot Detection Integrating Global and Local Information
- PSDet: Efficient and Universal Parking Slot Detection
parking lot image
- Automated Vehicle Parking Slot Detection System Using Deep Learning
- Automated Parking Space Detection Using Convolutional Neural Networks
- An Elaborative Study of Smart Parking Systems
- Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion
- Automatic Parking System Based on Improved Neural Network Algorithm and Intelligent Image Analysis
around view image
- awesome-parking-slot-detection
- VPS-Net
- context-based-parking-slot-detect
- Parking-slot-detection
- Parking-slot-dataset
- MarkToolForParkingLotPoint
object detection using yolo
around view image
parking lot image
- Searching for a Parking Spot? AI Got It
- AI Can Detect Open Parking Spaces
- Parking Lot Vehicle Detection Using Deep Learning
- Parking Space Detection Using Deep Learning
- Parking Occupancy Detection Using AI and ML
around view image
- [ps2.0] Tongji Parking-slot Dataset 2.0: A Large-scale Benchmark Dataset
- Context-Based Parking Slot Detect Dataset
Explanation about folders and files.
- data - contains the datasets, annotation files, and class details
- {dataset folder name}
- train
- val
- test
- train_annotation.txt
- val_annotation.txt
- test_annotation.txt
- ps_classes.txt
- {dataset folder name}
- dataloader
- dataloader.py - custom data generator
- loss
- loss_functional.py - loss is written in a function
- loss_subclass.py - loss is written under a class
- model
- darknet.py - backbone
- model_functional.py - functional model
- model_subclass.py - model sub-classing
- model_yolo3_tf2 - yolov3 model reference from yolov3-tf2
- model_data - contains the .cfg, .weights, .h5, font files
- model_img - contains the architecture images
- notebook - contains the jupyter / google colab notebook file
- utils
- callbacks.py
- dataloader.py - reference from yolov3-tf2
- utils.py
- utils_bbox.py
- utils_metric.py
- configs.py
- convert.py
- predict.py
- train.py
- convert0.py - reference from yolov3-tf2
- predict0.py - reference from yolov3-tf2
- train0.py - reference from yolov3-tf2
- psmat2txt.py - generates annotations in YOLO v3 Keras TXT format from mat files
- visbbox.py - visualise bounding boxes
Sample results of parking slot head detection with VPS-Net as reference
- find complete parking slot
- improve performance by referring other papers