opti_models VS tflite2tensorflow

Compare opti_models vs tflite2tensorflow and see what are their differences.

tflite2tensorflow

Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model. (by PINTO0309)
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opti_models tflite2tensorflow
1 2
55 249
- -
0.0 0.0
over 2 years ago over 1 year ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

opti_models

Posts with mentions or reviews of opti_models. We have used some of these posts to build our list of alternatives and similar projects.

tflite2tensorflow

Posts with mentions or reviews of tflite2tensorflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-20.

What are some alternatives?

When comparing opti_models and tflite2tensorflow you can also consider the following projects:

YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/