unicornwhodev/lite-rt_models_cadrylpro

Cadryl · LiteRT models by task

An Android studio for importing images, reviewing model proposals, correcting annotations and exporting datasets. 48 model groups · 99 LiteRT exports · 93 image / 6 audio.

Quick card

Field	Reference
Use	Choose a specialized inference model for one documented task.
Expected input	An image and its exact export configuration; audio uses a separate native frontend.
Example	Import a model/config pair, try a representative image, review and preserve human annotations.
Limits	Inference-only collection; benchmark scores do not establish accuracy on your photos or complete Release/device qualification.
Contract	Per-export catalogue · Import guide

Choose a variant · Resource navigation · Update log

15 task comparisons · All variants · JSON index

Task group	Available uses
Classification	Waste, materials, PCB1 anomalies, sharpness, clothing, fruit freshness, gestures, signed alphabet, indoor/outdoor scenes and Kuzushiji.
Detection	Helmets/heads/people and document text blocks.
Segmentation	Pothole foreground masks.
Points	Four document corners.
Audio	Spoken digits, with the exact audio frontend.

Use a matching pair

1. Retrieve the chosen .tflite and its exact .tflite.model_config.json at one immutable revision.
2. Import both into Cadryl; preserve labels, preprocessing, tensor outputs and thresholds.
3. Try a representative image, review proposals and preserve corrected human annotations.

Application · Downloads · Getting started · About Unicorn Who Dev

Evidence and remaining limits

The existing execution receipt reports 93 cloud image executions and 66/93 image variants executed on ARM64 Debug, with synthetic device inputs. Complete physical-device coverage and Release APK qualification remain open. These are execution checks, not representative photo accuracy or phone timing benchmarks.

The comparisons retain full-test scores, recorded intervals and exact source hashes. Historical scores without a public common-test identity are not ranked. Fashion-MNIST at 460 px remains deferred. No training, new evaluation or paid compute is started by this update.

General-purpose conversions · Audio frontend · Hashes · Attributions. Original corpus/checkpoint restrictions remain applicable; no new blanket weight licence is assigned.

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