Instructions to use camstack/camstack-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use camstack/camstack-models with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("camstack/camstack-models") - Notebooks
- Google Colab
- Kaggle
add vehicleClassification/vehicle-type-v1 small classifier (onnx+openvino+coreml+labels)
Browse files- vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1-labels.json +34 -0
- vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1.mlpackage/Data/com.apple.CoreML/model.mlmodel +3 -0
- vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1.mlpackage/Data/com.apple.CoreML/weights/weight.bin +3 -0
- vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1.mlpackage/Manifest.json +18 -0
- vehicleClassification/vehicle-type-v1/onnx/vehicle-type-v1-labels.json +34 -0
- vehicleClassification/vehicle-type-v1/onnx/vehicle-type-v1.onnx +3 -0
- vehicleClassification/vehicle-type-v1/openvino/vehicle-type-v1-labels.json +34 -0
- vehicleClassification/vehicle-type-v1/openvino/vehicle-type-v1.bin +3 -0
- vehicleClassification/vehicle-type-v1/openvino/vehicle-type-v1.xml +0 -0
- vehicleClassification/vehicle-type-v1/vehicle-type-v1-labels.json +34 -0
vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1-labels.json
ADDED
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{
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"labels": [
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"Ambulance",
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"Bicycle",
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"Bus",
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"Car",
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"Motorcycle",
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"Taxi",
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"Truck",
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"Van"
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],
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"input_size": 224,
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"num_classes": 8,
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| 14 |
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"preprocess": {
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"normalize": "imagenet",
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| 16 |
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"mean": [
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0.485,
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+
0.456,
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+
0.406
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],
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"std": [
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0.229,
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0.224,
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+
0.225
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],
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"channels": "RGB",
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"layout": "NCHW"
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},
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"arch": "mobilenet_v3_large",
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| 30 |
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"source": "torchvision IMAGENET1K_V2 fine-tuned on DrBimmer/vehicle-classification road subset",
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"license": "BSD-3-Clause (torchvision) / dataset per-source",
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"output": "logits (apply softmax)",
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"best_val_acc": 0.8938
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}
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vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1.mlpackage/Data/com.apple.CoreML/model.mlmodel
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:a555f0b87a195f725bf09ced2361ae3cb07542e5e379cbc1c98a168dc78c3756
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| 3 |
+
size 118233
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vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1.mlpackage/Data/com.apple.CoreML/weights/weight.bin
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:26cf66168010daa0a1d33a2fc12305e0e7465c977840861b4bf470c8cae8a7b8
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+
size 8409856
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vehicleClassification/vehicle-type-v1/coreml/vehicle-type-v1.mlpackage/Manifest.json
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{
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"fileFormatVersion": "1.0.0",
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"itemInfoEntries": {
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"B1DBCBF0-E693-4DDD-B03B-48C64BBF7110": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Specification",
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"name": "model.mlmodel",
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"path": "com.apple.CoreML/model.mlmodel"
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},
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"E1211D56-A8AD-44F0-81B4-5ED581D52CD1": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Weights",
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"name": "weights",
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"path": "com.apple.CoreML/weights"
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}
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},
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"rootModelIdentifier": "B1DBCBF0-E693-4DDD-B03B-48C64BBF7110"
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}
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vehicleClassification/vehicle-type-v1/onnx/vehicle-type-v1-labels.json
ADDED
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{
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"labels": [
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"Ambulance",
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"Bicycle",
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"Bus",
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"Car",
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"Motorcycle",
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| 8 |
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"Taxi",
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"Truck",
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| 10 |
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"Van"
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| 11 |
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],
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| 12 |
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"input_size": 224,
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"num_classes": 8,
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| 14 |
+
"preprocess": {
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| 15 |
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"normalize": "imagenet",
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| 16 |
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"mean": [
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| 17 |
+
0.485,
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| 18 |
+
0.456,
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| 19 |
+
0.406
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| 20 |
+
],
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| 21 |
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"std": [
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| 22 |
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0.229,
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| 23 |
+
0.224,
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+
0.225
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| 25 |
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],
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| 26 |
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"channels": "RGB",
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"layout": "NCHW"
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| 28 |
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},
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| 29 |
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"arch": "mobilenet_v3_large",
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| 30 |
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"source": "torchvision IMAGENET1K_V2 fine-tuned on DrBimmer/vehicle-classification road subset",
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| 31 |
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"license": "BSD-3-Clause (torchvision) / dataset per-source",
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| 32 |
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"output": "logits (apply softmax)",
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| 33 |
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"best_val_acc": 0.8938
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| 34 |
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}
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vehicleClassification/vehicle-type-v1/onnx/vehicle-type-v1.onnx
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:5153b77de54286bcfefddfdfec9e3c1101b10c30bc33e9181cf8c04e0156818f
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+
size 16844593
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vehicleClassification/vehicle-type-v1/openvino/vehicle-type-v1-labels.json
ADDED
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@@ -0,0 +1,34 @@
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+
{
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"labels": [
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| 3 |
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"Ambulance",
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| 4 |
+
"Bicycle",
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| 5 |
+
"Bus",
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| 6 |
+
"Car",
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| 7 |
+
"Motorcycle",
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| 8 |
+
"Taxi",
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| 9 |
+
"Truck",
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| 10 |
+
"Van"
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| 11 |
+
],
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| 12 |
+
"input_size": 224,
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| 13 |
+
"num_classes": 8,
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| 14 |
+
"preprocess": {
|
| 15 |
+
"normalize": "imagenet",
|
| 16 |
+
"mean": [
|
| 17 |
+
0.485,
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| 18 |
+
0.456,
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| 19 |
+
0.406
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| 20 |
+
],
|
| 21 |
+
"std": [
|
| 22 |
+
0.229,
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| 23 |
+
0.224,
|
| 24 |
+
0.225
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| 25 |
+
],
|
| 26 |
+
"channels": "RGB",
|
| 27 |
+
"layout": "NCHW"
|
| 28 |
+
},
|
| 29 |
+
"arch": "mobilenet_v3_large",
|
| 30 |
+
"source": "torchvision IMAGENET1K_V2 fine-tuned on DrBimmer/vehicle-classification road subset",
|
| 31 |
+
"license": "BSD-3-Clause (torchvision) / dataset per-source",
|
| 32 |
+
"output": "logits (apply softmax)",
|
| 33 |
+
"best_val_acc": 0.8938
|
| 34 |
+
}
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vehicleClassification/vehicle-type-v1/openvino/vehicle-type-v1.bin
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bf352f4a602d5e6ef5b6df5140972ef68e79076be397a90c10f1efdda59f4a1e
|
| 3 |
+
size 8424214
|
vehicleClassification/vehicle-type-v1/openvino/vehicle-type-v1.xml
ADDED
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The diff for this file is too large to render.
See raw diff
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vehicleClassification/vehicle-type-v1/vehicle-type-v1-labels.json
ADDED
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@@ -0,0 +1,34 @@
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| 1 |
+
{
|
| 2 |
+
"labels": [
|
| 3 |
+
"Ambulance",
|
| 4 |
+
"Bicycle",
|
| 5 |
+
"Bus",
|
| 6 |
+
"Car",
|
| 7 |
+
"Motorcycle",
|
| 8 |
+
"Taxi",
|
| 9 |
+
"Truck",
|
| 10 |
+
"Van"
|
| 11 |
+
],
|
| 12 |
+
"input_size": 224,
|
| 13 |
+
"num_classes": 8,
|
| 14 |
+
"preprocess": {
|
| 15 |
+
"normalize": "imagenet",
|
| 16 |
+
"mean": [
|
| 17 |
+
0.485,
|
| 18 |
+
0.456,
|
| 19 |
+
0.406
|
| 20 |
+
],
|
| 21 |
+
"std": [
|
| 22 |
+
0.229,
|
| 23 |
+
0.224,
|
| 24 |
+
0.225
|
| 25 |
+
],
|
| 26 |
+
"channels": "RGB",
|
| 27 |
+
"layout": "NCHW"
|
| 28 |
+
},
|
| 29 |
+
"arch": "mobilenet_v3_large",
|
| 30 |
+
"source": "torchvision IMAGENET1K_V2 fine-tuned on DrBimmer/vehicle-classification road subset",
|
| 31 |
+
"license": "BSD-3-Clause (torchvision) / dataset per-source",
|
| 32 |
+
"output": "logits (apply softmax)",
|
| 33 |
+
"best_val_acc": 0.8938
|
| 34 |
+
}
|