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AWS Rekognition DetectLabels Alternatives

AWS Rekognition's DetectLabels API enables you to identify objects and themes in images without prior training. Below, we list a series of alternatives that you can use to identify objects in images and videos.

All models listed below can be deployed on the edge (i.e. on NVIDIA Jetson or Raspberry Pi) or using a hosted, scalable API.
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Multimodal Model
Multimodal Model
Multimodal Model
Multimodal Model
PaliGemma

Model Size:

4000000000.0

MB

Parameters:

3 Billion

Architecture:

PaliGemma is a vision language model (VLM) by Google that has multimodal capabilities. Learn more »

Deploy on the edge and at scale with Roboflow Inference

Run model on videos with Roboflow Hosted Video Inference

How to train
Colab notebook
Jupyter notebook
View on GitHub
Video guide
Multimodal Model
Multimodal Model
Multimodal Model
Multimodal Model
Google Gemini

Model Size:

MB

Parameters:

Architecture:

Gemini is a family of Large Multimodal Models (LMMs) developed by Google Deepmind focused specifically on multimodality. Learn more »

Deploy on the edge and at scale with Roboflow Inference

Run model on videos with Roboflow Hosted Video Inference

How to train
Colab notebook
Jupyter notebook
View on GitHub
Video guide
Object Detection
Object Detection
Object Detection
Object Detection
DocTR

Model Size:

MB

Parameters:

Architecture:

DocTR is an Optical Character Recognition tool powered by deep learning. Learn more »

Deploy on the edge and at scale with Roboflow Inference

Run model on videos with Roboflow Hosted Video Inference

How to train
Colab notebook
Jupyter notebook
View on GitHub
Video guide
Object Detection
Object Detection
Object Detection
Object Detection
YOLOv8

Model Size:

68200000.0

MB

Parameters:

Architecture:

YOLO, CNN

YOLOv8 is a state-of-the-art object detection and image segmentation model created by Ultralytics, the developers of YOLOv5. Learn more »

Deploy on the edge and at scale with Roboflow Inference

Run model on videos with Roboflow Hosted Video Inference

How to train
Colab notebook
Jupyter notebook
View on GitHub
Video guide
Classification
Classification
Classification
Classification
OpenAI CLIP

Model Size:

MB

Parameters:

428000000.0

Architecture:

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. Learn more »

Deploy on the edge and at scale with Roboflow Inference

Run model on videos with Roboflow Hosted Video Inference

How to train
Colab notebook
Jupyter notebook
View on GitHub
Video guide

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