add model trained on the full dataset

app.py

@@ -7,7 +7,7 @@ from torchvision import transforms
 from transformers import SegformerForSemanticSegmentation
 
 
-MODEL_PATH="./best_model_test/"
+MODEL_PATH="./best_model_mixto/"
 
 device = torch.device("cpu")
 

best_model_mixto/config.json

@@ -0,0 +1,78 @@
+{
+  "_name_or_path": "nvidia/mit-b0",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 256,
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    32,
+    64,
+    160,
+    256
+  ],
+  "id2label": {
+    "0": "cordillera",
+    "1": "glaciar"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "cordillera": 0,
+    "glaciar": 1
+  },
+  "layer_norm_eps": 1e-06,
+  "mlp_ratios": [
+    4,
+    4,
+    4,
+    4
+  ],
+  "model_type": "segformer",
+  "num_attention_heads": [
+    1,
+    2,
+    5,
+    8
+  ],
+  "num_channels": 3,
+  "num_encoder_blocks": 4,
+  "patch_sizes": [
+    7,
+    3,
+    3,
+    3
+  ],
+  "reshape_last_stage": true,
+  "semantic_loss_ignore_index": 255,
+  "sr_ratios": [
+    8,
+    4,
+    2,
+    1
+  ],
+  "strides": [
+    4,
+    2,
+    2,
+    2
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.24.0"
+}

best_model_mixto/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08e13b24c6d6aebadfffbbc1a2a2f3a1de620baf1fb834aa098fb8f27eab5e34
+size 14929953