infery-examples
timm-flutter-pytorch-lite-blogpost
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infery-examples
timm-flutter-pytorch-lite-blogpost
- how to deploy object detection and image classification model in flutter?
- PyTorch at the Edge: Deploy 964 TIMM Models on Android with TorchScript
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PyTorch at the Edge: Deploying Over 964 TIMM Models on Android with TorchScript and Flutter.
Blog - https://dicksonneoh.com/portfolio/pytorch_at_the_edge_timm_torchscript_flutter/
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PyTorch at the Edge: Deploying Over 964 TIMM Models on Android with TorchScript and Flutter
GitHub Repo - https://github.com/dnth/timm-flutter-pytorch-lite-blogpost
What are some alternatives?
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
EfficientConformer - [ASRU 2021] Efficient Conformer: Progressive Downsampling and Grouped Attention for Automatic Speech Recognition
hand-gesture-recognition-mediapipe - This is a sample program that recognizes hand signs and finger gestures with a simple MLP using the detected key points. Handpose is estimated using MediaPipe.
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
fastT5 - ⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x.
notebooks - Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
x-stable-diffusion - Real-time inference for Stable Diffusion - 0.88s latency. Covers AITemplate, nvFuser, TensorRT, FlashAttention. Join our Discord communty: https://discord.com/invite/TgHXuSJEk6
seq_nms - PyTorch implementation of seq-nms
nebuly - The user analytics platform for LLMs
poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)
EdgeSAM - Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM"
computervision-recipes - Best Practices, code samples, and documentation for Computer Vision.