animalClassification/bird-classifier: AIY Vision Birds V1 (MobileNetV2), bird classifier
| Catalog id | bird-classifier (964 species plus background) |
| Upstream | Google AIY Vision birds_V1, published in https://github.com/google-coral/test_data |
| Obtained from | the TensorFlow model aiy/vision/classifier/birds_V1 (per the ONNX metadata) |
| Code licence | Apache-2.0 |
| Weights licence | Apache-2.0 (LICENSES/Apache-2.0.txt) |
| Training data | not stated upstream |
| CamStack modifications | converted from TensorFlow with tf2onnx; OpenVINO IR and CoreML derived from the ONNX; the Edge TPU build (tflite/) is the Google full-integer quantised TFLite of the same model, compiled with edgetpu_compiler 14 |
| Commercial use | permitted by Apache-2.0 |
Formats
| Format | File | Notes |
|---|---|---|
| ONNX | onnx/bird-classifier.onnx (+ bird-classifier-labels.json) |
fp32, NHWC, input x/255 |
| OpenVINO IR | openvino/bird-classifier.{xml,bin} |
from the ONNX |
| CoreML | coreml/bird-classifier.mlpackage |
from the ONNX |
| Coral Edge TPU | tflite/bird-classifier_edgetpu.tflite |
full-integer uint8; input raw 0..255 RGB (scale 1/128, zero point 128 in the graph); output [1,965] uint8 softmax, scale 1/256 — dequantise, do not re-softmax. All 65 operations on the Edge TPU, 3.75 MiB of parameter cache |
The Edge TPU file is built from mobilenet_v2_1.0_224_inat_bird_quant.tflite
(google-coral/test_data commit 104342d2, sha256 350fcd8c…04f9) by
scripts/build-bird-classifier-edgetpu.py in the CamStack repository. Every
compile writes a fresh random parameter-cache token, so a rebuild differs from
this file in those 16 bytes only. Labels: the ONNX folder's labels file (same
965 entries, same order).
CamStack redistributes the files in this folder; every change from the upstream is stated above. Converting a model does not change its licence. The collection statement is LICENSE; every model's attribution is in THIRD_PARTY_MODELS.md.