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gptkbp:instance_of
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gptkb:cosmic_ray_detector
|
|
gptkbp:application
|
gptkb:robotics
Autonomous vehicles
Surveillance systems
Retail analytics
Healthcare monitoring
|
|
gptkbp:architecture
|
gptkb:neural_networks
|
|
gptkbp:community_support
|
Active community on Git Hub
|
|
gptkbp:dependency
|
gptkb:Matplotlib
gptkb:Pandas
gptkb:Open_CV
gptkb:Sci_Py
gptkb:Num_Py
|
|
gptkbp:developed_by
|
gptkb:Ultralytics
|
|
gptkbp:evaluates
|
Precision
Recall
F1 score
Benchmarking on COCO
Speed vs accuracy trade-off
|
|
gptkbp:features
|
Quantization
Model pruning
Augmentation techniques
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
YOLOv5 Model
|
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gptkbp:input_output
|
gptkb:video
gptkb:JSON
gptkb:CSV
gptkb:Images
Bounding boxes and class probabilities
640x640
|
|
gptkbp:is_a_framework_for
|
gptkb:Py_Torch
|
|
gptkbp:language
|
gptkb:Python
|
|
gptkbp:latest_version
|
v5.0
|
|
gptkbp:license
|
GPL-3.0
|
|
gptkbp:losses
|
Cross-entropy loss
Io U loss
|
|
gptkbp:model
|
gptkb:YOLOv5l
gptkb:YOLOv5m
gptkb:YOLOv5s
gptkb:YOLOv5x
Varies by version
|
|
gptkbp:performance
|
m AP (mean Average Precision)
|
|
gptkbp:predecessor
|
YOLOv4 Model
|
|
gptkbp:provides_information_on
|
gptkb:COCO_dataset
|
|
gptkbp:release_date
|
June 2020
|
|
gptkbp:repository
|
gptkb:Git_Hub
|
|
gptkbp:successor
|
YOLOv6 Model
|
|
gptkbp:supports
|
GPU acceleration
CPU inference
Multi-class detection
|
|
gptkbp:training
|
Supervised learning
Varies by hardware
|
|
gptkbp:training_programs
|
gptkb:Google_Colab
Cloud services
Local machine
|
|
gptkbp:tutorials
|
Available online
|
|
gptkbp:uses
|
Transfer learning
Real-time object detection
|
|
gptkbp:written_in
|
gptkb:Python
|
|
gptkbp:bfsParent
|
gptkb:Ultralytics
|
|
gptkbp:bfsLayer
|
7
|