iTeXSnip

Image -> LaTeX

Works with handwritten formulae as well!

TODO

V1

• Rating API
• Preferences
  • Model load preferences
  • Detailed view preferences
  • Rating API server
• Complete Detailed Snippet View

V2

• Math Solver
• TeX Snippet Editor
• Image Export
• UI Overhaul
• Optimizations

Misc

Quantization

You can download and replace the quantized files with non-quantized versions from here

Encoder Model

python -m onnxruntime.quantization.preprocess --input  iTexSnip/models/encoder_model.onnx --output  encoder-infer.onnx

import onnx
from onnxruntime.quantization import quantize_dynamic, QuantType
og = "encoder-infer.onnx"
quant = "encoder-quant.onnx"
quantized_model = quantize_dynamic(og, quant, nodes_to_exclude=['/embeddings/patch_embeddings/projection/Conv'])

It might be better if we quantize the encoder using static quantization.

Decoder Model

python -m onnxruntime.quantization.preprocess --input  iTexSnip/models/decoder_model.onnx --output  decoder-infer.onnx

import onnx
from onnxruntime.quantization import quantize_dynamic, QuantType
og = "decoder-infer.onnx"
quant = "decoder-quant.onnx"
quantized_model = quantize_dynamic(og, quant)