Models
MobileNet SSD v2 vs. OpenAI CLIP

MobileNet SSD v2 vs. OpenAI CLIP

Both MobileNet SSD v2 and OpenAI CLIP are commonly used in computer vision projects. Below, we compare and contrast MobileNet SSD v2 and OpenAI CLIP.

Models

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MobileNet SSD v2

This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.
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OpenAI CLIP

CLIP (Contrastive Language-Image Pre-Training) is an impressive multimodal zero-shot image classifier that achieves impressive results in a wide range of domains with no fine-tuning. It applies the recent advancements in large-scale transformers like GPT-3 to the vision arena.
Model Type
Object Detection
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Classification
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Model Features
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Item 2 Info
Architecture
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Frameworks
TensorFlow 1.5
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
81+
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21.4k+
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License
MIT
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MIT
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Training Notebook

Compare MobileNet SSD v2 and OpenAI CLIP with Autodistill

Compare MobileNet SSD v2 vs. OpenAI CLIP

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.