add files from colab

app.py

@@ -0,0 +1,36 @@
+import datasets
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+
+dataset = datasets.load_dataset('beans')
+
+extractor = AutoFeatureExtractor.from_pretrained("saved_model_files")
+model = AutoModelForImageClassification.from_pretrained("saved_model_files")
+
+labels = dataset['train'].features['labels'].names
+
+def classify(im):
+  features = feature_extractor(im, return_tensors='pt')
+  logits = model(features["pixel_values"])[-1]
+  probability = torch.nn.functional.softmax(logits, dim=-1)
+  probs = probability[0].detach().numpy()
+  confidences = {label: float(probs[i]) for i, label in enumerate(labels)} 
+  return confidences
+
+import gradio as gr
+
+interface = gr.Interface(fn=classify, inputs="image", outputs="label", 
+                         examples=[
+                             ["https://images.unsplash.com/photo-1550147760-44c9966d6bc7?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxzZWFyY2h8Nnx8bGVhZnxlbnwwfHwwfHw%3D&auto=format&fit=crop&w=800&q=60"],
+                             ["https://images.unsplash.com/photo-1525498128493-380d1990a112?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MTd8fGxlYWZ8ZW58MHx8MHx8&auto=format&fit=crop&w=800&q=60"],
+                             ["https://apps.lucidcentral.org/pppw_v10/images/entities/bean_angular_leaf_spot_216/angularspot1.jpg"],
+                             ["https://extension.umn.edu/sites/extension.umn.edu/files/beans-viral-diseases-2.jpg"],
+                             ["http://1.bp.blogspot.com/-CcMICF_A1CI/UHKSvTV2k2I/AAAAAAAAHI0/TlFMGU8RpYQ/s1600/DSCF9698.JPG"],
+                             ["https://www.garden.eco/wp-content/uploads/2017/12/bean-leaves.jpg"],
+                             ["https://apps.lucidcentral.org/pppw_v10/images/entities/bean_angular_leaf_spot_216/angularspot1.jpg"]
+
+
+                         ],
+                         title="🍃 Bean Leaf Image Classification",
+                         description="Based on a leaf image, the goal is to predict the disease type (Angular Leaf Spot and Bean Rust), if any.",)
+
+interface.launch(debug=True)

requirements.txt

@@ -0,0 +1,2 @@
+torch
+transformers

saved_model_files/config.json

@@ -0,0 +1,34 @@
+{
+  "_name_or_path": "google/vit-base-patch16-224",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "angular_leaf_spot",
+    "1": "bean_rust",
+    "2": "healthy"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "angular_leaf_spot": "0",
+    "bean_rust": "1",
+    "healthy": "2"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.22.1"
+}

saved_model_files/preprocessor_config.json

@@ -0,0 +1,17 @@
+{
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "ViTFeatureExtractor",
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "size": 224
+}

saved_model_files/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a8a00185935123b602150d9bb505a0d51eca2e815f1bb6e461973be2d2d653a6
+size 343270065

saved_model_files/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d735a4e0301637cf2a8dbfb9b3200d5380d1151359b09e51fa21a9ac5e53a434
+size 3375