TransNetV2 (ONNX)
transnetv2.onnx — an ONNX export of TransNetV2 for shot boundary
detection (finding the hard cuts and gradual transitions between the shots of
a video). Runs client-side with onnxruntime-web.
Inputs / outputs
- Input:
inputfloat32[1, 100, 27, 48, 3]— a window of 100 frames, each resized to 48x27, RGB, values 0..255 (the graph divides by 255 itself). - Outputs: two float32
[1, 100, 1]per-frame probabilities (the sigmoid is already applied):- single-frame — the frame a cut lands on (the last frame of the outgoing shot);
- many-hot — every frame inside a transition (dissolve, fade, …).
- Upstream inference slides the window by 50 frames with 25 frames of context either side and keeps the middle 50 predictions of each window.
Provenance & license
- Model: TransNetV2 — TransNet V2: An effective deep network architecture
for fast shot transition detection (Souček & Lokoč, 2020),
soCzech/TransNetV2. Code and model
weights are released under the MIT license
(
Copyright (c) 2020 Tomáš Souček), included here asLICENSE. - ONNX export: elya5/transnetv2 (MIT), mirrored verbatim.