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Detr Finetuned Trashify Box Detector With Data Aug
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Detr Finetuned Trashify Box Detector With Data Aug
Developed by mrdbourke
This model is a fine-tuned object detection model based on microsoft/conditional-detr-resnet-50, specifically designed for trash detection tasks, with data augmentation techniques applied during training.
Downloads 19
Release Time : 11/18/2024
Model Overview
This is an object detection model based on the DETR architecture, fine-tuned specifically for trash detection tasks. The model achieved a loss value of 1.0704 on the evaluation set.
Model Features
Data Augmentation Training
Data augmentation techniques were used during training to improve the model's generalization capability.
DETR Architecture
An end-to-end object detection model based on Transformer architecture, eliminating the need for complex post-processing.
ResNet-50 Backbone
Uses ResNet-50 as the feature extractor, balancing performance and computational efficiency.
Model Capabilities
Object Detection
Trash Recognition
Bounding Box Prediction
Use Cases
Environmental Management
Waste Sorting System
An intelligent system for automatic trash identification and classification
Cleaning Robot Vision
Provides trash detection capabilities for cleaning robots
Smart Monitoring
Public Space Trash Monitoring
Monitors trash accumulation in public spaces
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