add model trained on the full dataset
Browse files- app.py +1 -1
- best_model_mixto/config.json +78 -0
- best_model_mixto/pytorch_model.bin +3 -0
app.py
CHANGED
@@ -7,7 +7,7 @@ from torchvision import transforms
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from transformers import SegformerForSemanticSegmentation
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-
MODEL_PATH="./
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device = torch.device("cpu")
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from transformers import SegformerForSemanticSegmentation
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MODEL_PATH="./best_model_mixto/"
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device = torch.device("cpu")
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best_model_mixto/config.json
ADDED
@@ -0,0 +1,78 @@
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{
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"_name_or_path": "nvidia/mit-b0",
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"architectures": [
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"SegformerForSemanticSegmentation"
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],
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"attention_probs_dropout_prob": 0.0,
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"classifier_dropout_prob": 0.1,
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"decoder_hidden_size": 256,
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"depths": [
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2,
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2,
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2,
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2
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],
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"downsampling_rates": [
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1,
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4,
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8,
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16
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],
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"drop_path_rate": 0.1,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_sizes": [
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32,
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64,
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160,
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256
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],
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"id2label": {
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"0": "cordillera",
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"1": "glaciar"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"label2id": {
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"cordillera": 0,
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"glaciar": 1
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},
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"layer_norm_eps": 1e-06,
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"mlp_ratios": [
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4,
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4,
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4,
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4
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],
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"model_type": "segformer",
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"num_attention_heads": [
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1,
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2,
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5,
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8
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],
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"num_channels": 3,
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"num_encoder_blocks": 4,
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"patch_sizes": [
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7,
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3,
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3,
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3
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],
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"reshape_last_stage": true,
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"semantic_loss_ignore_index": 255,
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"sr_ratios": [
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8,
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4,
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2,
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1
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],
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"strides": [
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4,
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2,
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2,
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2
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],
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"torch_dtype": "float32",
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"transformers_version": "4.24.0"
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}
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best_model_mixto/pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:08e13b24c6d6aebadfffbbc1a2a2f3a1de620baf1fb834aa098fb8f27eab5e34
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size 14929953
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