Upload folder using huggingface_hub
Browse files- README.md +33 -0
- config.json +99 -0
- image_converter.json +33 -0
- metadata.json +6 -0
- model.weights.h5 +3 -0
- preprocessor.json +51 -0
- task.json +162 -0
- task.weights.h5 +3 -0
README.md
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---
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library_name: keras-hub
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---
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This is a [`EfficientNet` model](https://keras.io/api/keras_hub/models/efficient_net) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
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This model is related to a `ImageClassifier` task.
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Model config:
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* **name:** efficient_net_backbone
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* **trainable:** True
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* **width_coefficient:** 1.0
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* **depth_coefficient:** 1.0
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* **dropout:** 0
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* **depth_divisor:** 8
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* **min_depth:** None
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* **activation:** swish
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* **input_shape:** [None, None, 3]
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* **stackwise_kernel_sizes:** [3, 3, 5, 3, 5, 5, 3]
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* **stackwise_num_repeats:** [1, 2, 2, 3, 3, 4, 1]
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* **stackwise_input_filters:** [32, 16, 24, 40, 80, 112, 192]
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* **stackwise_output_filters:** [16, 24, 40, 80, 112, 192, 320]
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* **stackwise_expansion_ratios:** [1, 6, 6, 6, 6, 6, 6]
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* **stackwise_squeeze_and_excite_ratios:** [0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25]
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* **stackwise_strides:** [1, 2, 2, 2, 1, 2, 1]
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* **stackwise_block_types:** ['v1', 'v1', 'v1', 'v1', 'v1', 'v1', 'v1']
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* **include_stem_padding:** True
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* **use_depth_divisor_as_min_depth:** True
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* **cap_round_filter_decrease:** True
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* **stem_conv_padding:** valid
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* **batch_norm_momentum:** 0.9
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* **batch_norm_epsilon:** 1e-05
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* **projection_activation:** None
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This model card has been generated automatically and should be completed by the model author. See [Model Cards documentation](https://huggingface.co/docs/hub/model-cards) for more information.
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config.json
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{
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"module": "keras_hub.src.models.efficientnet.efficientnet_backbone",
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"class_name": "EfficientNetBackbone",
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| 4 |
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"config": {
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| 5 |
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"name": "efficient_net_backbone",
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| 6 |
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"trainable": true,
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| 7 |
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"width_coefficient": 1.0,
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| 8 |
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"depth_coefficient": 1.0,
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| 9 |
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"dropout": 0,
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| 10 |
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"depth_divisor": 8,
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| 11 |
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"min_depth": null,
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"activation": "swish",
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"input_shape": [
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null,
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null,
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3
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],
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"stackwise_kernel_sizes": [
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3,
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3,
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5,
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3,
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5,
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5,
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3
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],
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| 27 |
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"stackwise_num_repeats": [
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1,
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2,
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2,
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3,
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3,
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4,
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1
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| 35 |
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],
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| 36 |
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"stackwise_input_filters": [
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32,
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16,
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24,
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40,
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80,
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112,
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192
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],
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"stackwise_output_filters": [
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16,
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24,
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40,
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80,
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+
112,
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192,
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320
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],
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"stackwise_expansion_ratios": [
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1,
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6,
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+
6,
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+
6,
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+
6,
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+
6,
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+
6
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],
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| 63 |
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"stackwise_squeeze_and_excite_ratios": [
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0.25,
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0.25,
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+
0.25,
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| 67 |
+
0.25,
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+
0.25,
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| 69 |
+
0.25,
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| 70 |
+
0.25
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| 71 |
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],
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| 72 |
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"stackwise_strides": [
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1,
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2,
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2,
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2,
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1,
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2,
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1
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| 80 |
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],
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| 81 |
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"stackwise_block_types": [
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"v1",
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"v1",
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"v1",
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| 85 |
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"v1",
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| 86 |
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"v1",
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| 87 |
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"v1",
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| 88 |
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"v1"
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| 89 |
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],
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| 90 |
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"include_stem_padding": true,
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| 91 |
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"use_depth_divisor_as_min_depth": true,
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| 92 |
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"cap_round_filter_decrease": true,
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| 93 |
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"stem_conv_padding": "valid",
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| 94 |
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"batch_norm_momentum": 0.9,
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| 95 |
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"batch_norm_epsilon": 1e-05,
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| 96 |
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"projection_activation": null
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| 97 |
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},
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| 98 |
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"registered_name": "keras_hub>EfficientNetBackbone"
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}
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image_converter.json
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{
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| 2 |
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"module": "keras_hub.src.models.efficientnet.efficientnet_image_converter",
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| 3 |
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"class_name": "EfficientNetImageConverter",
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| 4 |
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"config": {
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| 5 |
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"name": "efficient_net_image_converter",
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| 6 |
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"trainable": true,
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| 7 |
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"dtype": {
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| 8 |
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"module": "keras",
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| 9 |
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"class_name": "DTypePolicy",
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| 10 |
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"config": {
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| 11 |
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"name": "float32"
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| 12 |
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},
|
| 13 |
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"registered_name": null
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| 14 |
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},
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| 15 |
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"image_size": [
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| 16 |
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224,
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| 17 |
+
224
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| 18 |
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],
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| 19 |
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"scale": [
|
| 20 |
+
0.00784313725490196,
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| 21 |
+
0.00784313725490196,
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| 22 |
+
0.00784313725490196
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| 23 |
+
],
|
| 24 |
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"offset": [
|
| 25 |
+
-1.0,
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| 26 |
+
-1.0,
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| 27 |
+
-1.0
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| 28 |
+
],
|
| 29 |
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"interpolation": "bicubic",
|
| 30 |
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"crop_to_aspect_ratio": true
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| 31 |
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},
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| 32 |
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"registered_name": "keras_hub>EfficientNetImageConverter"
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| 33 |
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}
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metadata.json
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{
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| 2 |
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"keras_version": "3.5.0",
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| 3 |
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"keras_hub_version": "0.17.0.dev0",
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| 4 |
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"parameter_count": 4049564,
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| 5 |
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"date_saved": "2024-10-31@14:48:13"
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}
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model.weights.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:514f14c90bd27f0b91116be20f961239a0a09a8e5e17741de4c69fad49b1138d
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| 3 |
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size 16772088
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preprocessor.json
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{
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| 2 |
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"module": "keras_hub.src.models.efficientnet.efficientnet_image_classifier_preprocessor",
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| 3 |
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"class_name": "EfficientNetImageClassifierPreprocessor",
|
| 4 |
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"config": {
|
| 5 |
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"name": "efficient_net_image_classifier_preprocessor",
|
| 6 |
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"trainable": true,
|
| 7 |
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"dtype": {
|
| 8 |
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"module": "keras",
|
| 9 |
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"class_name": "DTypePolicy",
|
| 10 |
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"config": {
|
| 11 |
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"name": "float32"
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| 12 |
+
},
|
| 13 |
+
"registered_name": null
|
| 14 |
+
},
|
| 15 |
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"image_converter": {
|
| 16 |
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"module": "keras_hub.src.models.efficientnet.efficientnet_image_converter",
|
| 17 |
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"class_name": "EfficientNetImageConverter",
|
| 18 |
+
"config": {
|
| 19 |
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"name": "efficient_net_image_converter",
|
| 20 |
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"trainable": true,
|
| 21 |
+
"dtype": {
|
| 22 |
+
"module": "keras",
|
| 23 |
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"class_name": "DTypePolicy",
|
| 24 |
+
"config": {
|
| 25 |
+
"name": "float32"
|
| 26 |
+
},
|
| 27 |
+
"registered_name": null
|
| 28 |
+
},
|
| 29 |
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"image_size": [
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| 30 |
+
224,
|
| 31 |
+
224
|
| 32 |
+
],
|
| 33 |
+
"scale": [
|
| 34 |
+
0.00784313725490196,
|
| 35 |
+
0.00784313725490196,
|
| 36 |
+
0.00784313725490196
|
| 37 |
+
],
|
| 38 |
+
"offset": [
|
| 39 |
+
-1.0,
|
| 40 |
+
-1.0,
|
| 41 |
+
-1.0
|
| 42 |
+
],
|
| 43 |
+
"interpolation": "bicubic",
|
| 44 |
+
"crop_to_aspect_ratio": true
|
| 45 |
+
},
|
| 46 |
+
"registered_name": "keras_hub>EfficientNetImageConverter"
|
| 47 |
+
},
|
| 48 |
+
"config_file": "preprocessor.json"
|
| 49 |
+
},
|
| 50 |
+
"registered_name": "keras_hub>EfficientNetImageClassifierPreprocessor"
|
| 51 |
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}
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task.json
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|
| 1 |
+
{
|
| 2 |
+
"module": "keras_hub.src.models.efficientnet.efficientnet_image_classifier",
|
| 3 |
+
"class_name": "EfficientNetImageClassifier",
|
| 4 |
+
"config": {
|
| 5 |
+
"backbone": {
|
| 6 |
+
"module": "keras_hub.src.models.efficientnet.efficientnet_backbone",
|
| 7 |
+
"class_name": "EfficientNetBackbone",
|
| 8 |
+
"config": {
|
| 9 |
+
"name": "efficient_net_backbone",
|
| 10 |
+
"trainable": true,
|
| 11 |
+
"width_coefficient": 1.0,
|
| 12 |
+
"depth_coefficient": 1.0,
|
| 13 |
+
"dropout": 0,
|
| 14 |
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"depth_divisor": 8,
|
| 15 |
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"min_depth": null,
|
| 16 |
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"activation": "swish",
|
| 17 |
+
"input_shape": [
|
| 18 |
+
null,
|
| 19 |
+
null,
|
| 20 |
+
3
|
| 21 |
+
],
|
| 22 |
+
"stackwise_kernel_sizes": [
|
| 23 |
+
3,
|
| 24 |
+
3,
|
| 25 |
+
5,
|
| 26 |
+
3,
|
| 27 |
+
5,
|
| 28 |
+
5,
|
| 29 |
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3
|
| 30 |
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],
|
| 31 |
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"stackwise_num_repeats": [
|
| 32 |
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1,
|
| 33 |
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2,
|
| 34 |
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2,
|
| 35 |
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3,
|
| 36 |
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3,
|
| 37 |
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4,
|
| 38 |
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1
|
| 39 |
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],
|
| 40 |
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"stackwise_input_filters": [
|
| 41 |
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32,
|
| 42 |
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16,
|
| 43 |
+
24,
|
| 44 |
+
40,
|
| 45 |
+
80,
|
| 46 |
+
112,
|
| 47 |
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192
|
| 48 |
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],
|
| 49 |
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"stackwise_output_filters": [
|
| 50 |
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16,
|
| 51 |
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24,
|
| 52 |
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40,
|
| 53 |
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80,
|
| 54 |
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112,
|
| 55 |
+
192,
|
| 56 |
+
320
|
| 57 |
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],
|
| 58 |
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"stackwise_expansion_ratios": [
|
| 59 |
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1,
|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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6
|
| 66 |
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],
|
| 67 |
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"stackwise_squeeze_and_excite_ratios": [
|
| 68 |
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0.25,
|
| 69 |
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0.25,
|
| 70 |
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0.25,
|
| 71 |
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0.25,
|
| 72 |
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0.25,
|
| 73 |
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0.25,
|
| 74 |
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0.25
|
| 75 |
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],
|
| 76 |
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"stackwise_strides": [
|
| 77 |
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1,
|
| 78 |
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2,
|
| 79 |
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2,
|
| 80 |
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|
| 81 |
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1,
|
| 82 |
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2,
|
| 83 |
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1
|
| 84 |
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],
|
| 85 |
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"stackwise_block_types": [
|
| 86 |
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"v1",
|
| 87 |
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"v1",
|
| 88 |
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"v1",
|
| 89 |
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"v1",
|
| 90 |
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"v1",
|
| 91 |
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"v1",
|
| 92 |
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"v1"
|
| 93 |
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],
|
| 94 |
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"include_stem_padding": true,
|
| 95 |
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"use_depth_divisor_as_min_depth": true,
|
| 96 |
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"cap_round_filter_decrease": true,
|
| 97 |
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"stem_conv_padding": "valid",
|
| 98 |
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"batch_norm_momentum": 0.9,
|
| 99 |
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"batch_norm_epsilon": 1e-05,
|
| 100 |
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"projection_activation": null
|
| 101 |
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},
|
| 102 |
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"registered_name": "keras_hub>EfficientNetBackbone"
|
| 103 |
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},
|
| 104 |
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"preprocessor": {
|
| 105 |
+
"module": "keras_hub.src.models.efficientnet.efficientnet_image_classifier_preprocessor",
|
| 106 |
+
"class_name": "EfficientNetImageClassifierPreprocessor",
|
| 107 |
+
"config": {
|
| 108 |
+
"name": "efficient_net_image_classifier_preprocessor",
|
| 109 |
+
"trainable": true,
|
| 110 |
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"dtype": {
|
| 111 |
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"module": "keras",
|
| 112 |
+
"class_name": "DTypePolicy",
|
| 113 |
+
"config": {
|
| 114 |
+
"name": "float32"
|
| 115 |
+
},
|
| 116 |
+
"registered_name": null
|
| 117 |
+
},
|
| 118 |
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"image_converter": {
|
| 119 |
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"module": "keras_hub.src.models.efficientnet.efficientnet_image_converter",
|
| 120 |
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"class_name": "EfficientNetImageConverter",
|
| 121 |
+
"config": {
|
| 122 |
+
"name": "efficient_net_image_converter",
|
| 123 |
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"trainable": true,
|
| 124 |
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"dtype": {
|
| 125 |
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"module": "keras",
|
| 126 |
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"class_name": "DTypePolicy",
|
| 127 |
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"config": {
|
| 128 |
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"name": "float32"
|
| 129 |
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},
|
| 130 |
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"registered_name": null
|
| 131 |
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},
|
| 132 |
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"image_size": [
|
| 133 |
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224,
|
| 134 |
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224
|
| 135 |
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],
|
| 136 |
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"scale": [
|
| 137 |
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0.00784313725490196,
|
| 138 |
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0.00784313725490196,
|
| 139 |
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|
| 140 |
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],
|
| 141 |
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"offset": [
|
| 142 |
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-1.0,
|
| 143 |
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-1.0,
|
| 144 |
+
-1.0
|
| 145 |
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],
|
| 146 |
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"interpolation": "bicubic",
|
| 147 |
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"crop_to_aspect_ratio": true
|
| 148 |
+
},
|
| 149 |
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"registered_name": "keras_hub>EfficientNetImageConverter"
|
| 150 |
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},
|
| 151 |
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"config_file": "preprocessor.json"
|
| 152 |
+
},
|
| 153 |
+
"registered_name": "keras_hub>EfficientNetImageClassifierPreprocessor"
|
| 154 |
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},
|
| 155 |
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"name": "efficient_net_image_classifier",
|
| 156 |
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"num_classes": 1000,
|
| 157 |
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"pooling": "avg",
|
| 158 |
+
"activation": null,
|
| 159 |
+
"dropout": 0.0
|
| 160 |
+
},
|
| 161 |
+
"registered_name": "keras_hub>EfficientNetImageClassifier"
|
| 162 |
+
}
|
task.weights.h5
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:65259ddbe35fd143645cd9a21cab7c9c806a2800ea00009786525598c46a26a5
|
| 3 |
+
size 21913376
|