Create app.py

app.py

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+import numpy as np
+from PIL import Image
+from tkinter import Tk, filedialog
+from transformers import AutoModelForImageClassification, AutoFeatureExtractor
+
+# Load the model and feature extractor from Hugging Face
+MODEL_NAME = "shaktibiplab/Animal-Classification"
+model = AutoModelForImageClassification.from_pretrained(MODEL_NAME)
+extractor = AutoFeatureExtractor.from_pretrained(MODEL_NAME)
+
+# Function to load and preprocess the image
+def load_and_preprocess_image(image_path):
+    image = Image.open(image_path).convert("RGB")
+    return image
+
+# Function to classify the image
+def classify_image(image_path):
+    image = load_and_preprocess_image(image_path)
+    inputs = extractor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    return model.config.id2label[predicted_class_idx]
+
+# Main program with file upload dialog
+if __name__ == "__main__":
+    root = Tk()
+    root.withdraw()  # Hide the main tkinter window
+    print("Please select an image file.")
+    
+    # Open a file dialog to select the image
+    image_path = filedialog.askopenfilename(
+        title="Select an Image",
+        filetypes=[("Image Files", "*.jpg *.jpeg *.png *.bmp *.tiff")]
+    )
+    
+    if image_path:
+        try:
+            predicted_class = classify_image(image_path)
+            print(f"Predicted Class: {predicted_class}")
+        except Exception as e:
+            print(f"Error: {e}")
+    else:
+        print("No file selected.")