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isnet-general-use.onnx distributed by the
rembg project (MIT); original
weights and architecture by Xuebin Qin et al. (DIS, Apache-2.0).output_image
(stage-1 sigmoid probability map). fp16 and dynamic-int8 (q8) variants
were generated with the official Transformers.js conversion scripts.input_image: float32 [1, 3, 1024, 1024], RGB,
normalized as x / 255 - 0.5 (mean 0.5, std 1.0).output_image: float32 [1, 1, 1024, 1024], sigmoid
probabilities. Min-max normalize per image for an alpha matte
(as done by rembg).onnx/model.onnx - fp32 (aux outputs stripped)onnx/model_fp16.onnx - fp16onnx/model_quantized.onnx - dynamic int8 (q8)