Add all files

README.md

@@ -1,13 +1,26 @@
 ---
-title: ImageClassification With ViT
-emoji: 🦀
+title: Image Classification with ViT
+emoji: 🖼️
 colorFrom: yellow
-colorTo: purple
+colorTo: red
 sdk: gradio
 sdk_version: 5.11.0
 app_file: app.py
 pinned: false
 license: mit
+tags:
+  - image-classification
+  - vision
+  - transformers
+  - vit
+  - deep-learning
+  - gradio
+datasets:
+  - imagenet-1k
+  - cifar10
+  - cifar100
+models:
+  - google/vit-base-patch16-224
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from PIL import Image
+
+# Load model and feature extractor
+model_name = "google/vit-base-patch16-224"
+model = AutoModelForImageClassification.from_pretrained(model_name)
+feature_extractor = AutoFeatureExtractor.from_pretrained(model_name)
+
+# Define the prediction function
+def classify_image(image):
+    inputs = feature_extractor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    label = model.config.id2label[predicted_class_idx]
+    return f"Predicted Class: {label}"
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Image Classification App",
+    description="Upload an image to classify it using the Vision Transformer model.",
+)
+
+# Launch the app
+if __name__ == "__main__":
+    interface.launch()

requirements.txt

@@ -0,0 +1,4 @@
+torch
+gradio
+transformers
+pillow