Models
Faster R-CNN vs. YOLOv4 Tiny

Faster R-CNN vs. YOLOv4 Tiny

Both Faster R-CNN and YOLOv4 Tiny are commonly used in computer vision projects. Below, we compare and contrast Faster R-CNN and YOLOv4 Tiny.

Models

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Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.
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YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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ResNet-D, YOLO
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Frameworks
TensorFlow 1.5
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Darknet
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
7.5k+
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License
MIT
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YOLO
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Training Notebook

Compare Faster R-CNN and YOLOv4 Tiny with Autodistill

Compare Faster R-CNN vs. YOLOv4 Tiny

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.