20 docs tagged with "SL1600"

A preprocessing model to convert NV12 formatted images from 1920x1080 resolution to RGB format at the same resolution.

A preprocessing model to convert NV12 formatted images from 1920x1080 resolution to RGB format at 224x224 resolution.

A preprocessing model to convert NV12 formatted images from 1920x1080 resolution to RGB format at 640x360 resolution.

A quantized Inception V4 model optimized for image classification on ImageNet at 299x299 resolution.

A MobileNet V1 model with a 0.25 width multiplier optimized for image classification on ImageNet at 224x224 resolution.

A quantized MobileNet V1 model with a 0.25 width multiplier optimized for image classification on ImageNet at 224x224 resolution.

A MobileNet V2 model with a 1.0 width multiplier optimized for image classification on ImageNet at 224x224 resolution.

A quantized MobileNet V2 model with a 1.0 width multiplier optimized for image classification on ImageNet at 224x224 resolution.

A lightweight MobileNet model optimized for people detection on high-resolution images.

A MobileNet model optimized for object detection on the COCO dataset with full resolution at 224x224 and 80 classes.

A PoseNet model using MobileNet architecture with 75% width multiplier for efficient body pose estimation.

A quantized PoseNet model using MobileNet architecture with 75% width multiplier for efficient and optimized body pose estimation.

A fast super-resolution model converting YUV images from 1280x720 to 3840x2160 resolution.

A fast super-resolution model converting YUV images from 1920x1080 to 3840x2160 resolution.

A QDEO-based super-resolution model converting YUV images from 1280x720 to 3840x2160 resolution.

A QDEO-based super-resolution model converting YUV images from 1920x1080 to 3840x2160 resolution.

A YOLOv5m model for object detection optimized for 640x480 resolution, offering a balance between speed and accuracy.

A YOLOv5s model for object detection optimized for 640x480 resolution, suitable for real-time applications.

A YOLOv5s model specialized for face detection, optimized for 640x480 resolution using ONNX with mixed quantization.

A YOLOv8s model specialized for body pose estimation, optimized for real-time applications.