Update app.py

app.py

@@ -1,10 +1,9 @@
 import gradio as gr
 import tensorflow as tf
 from tensorflow.keras.models import load_model
-from tensorflow.keras.preprocessing.image import img_to_array, load_img
+from tensorflow.keras.preprocessing.image import img_to_array
 import numpy as np
 import os
-import requests
 
 # Load your model and tokenizer
 labels = {
@@ -20,7 +19,6 @@ hierarchical_models = {}
 model_path = r"inceptionv3_class.h5"
 hierarchical_models['class'] = load_model(model_path)
 
-    
 def load_and_preprocess_image(image, target_size=(299, 299)):
     img_array = img_to_array(image)
     img_array = np.expand_dims(img_array, axis=0)
@@ -35,22 +33,38 @@ def predict(image):
     class_preds = hierarchical_models['class'].predict(image_array)
     class_idx = np.argmax(class_preds)
     class_label = labels['class'][class_idx]
-
+    class_confidence = class_preds[0][class_idx]
+    
     # Predict species level
     hierarchical_models[class_label] = load_model(f"inceptionv3_{class_label}.h5")
     species_preds = hierarchical_models[class_label].predict(image_array)
     species_idx = np.argmax(species_preds)
     species_label = labels[class_label][species_idx]
-    return class_label,species_label
+    species_confidence = species_preds[0][species_idx]
+    
+    return {
+        "Class": f"{class_label} ({class_confidence*100:.2f}%)",
+        "Species": f"{species_label} ({species_confidence*100:.2f}%)"
+    }
+
+# Sample images (you can add paths to images here)
+# sample_images = [
+#     ("Sample Amphibia", "path/to/amphibia.jpg"),
+#     ("Sample Aves", "path/to/aves.jpg"),
+#     ("Sample Mammalia", "path/to/mammalia.jpg"),
+#     # Add more sample images as needed
+# ]
 
 # Create Gradio interface
 iface = gr.Interface(
     fn=predict,
     inputs=gr.Image(type="pil"),
-    outputs=[gr.Label(label="class_label"), gr.Label(label="species_label")],
+    outputs=[gr.Label(label="Class Prediction"), gr.Label(label="Species Prediction")],
+    # examples=sample_images,
     title="Image Classification",
-    description="Upload an image to classify it into species and class level."
+    description="Upload an image to classify it into species and class level.",
+    interpretation="default"
 )
 
 # Launch the interface
-iface.launch()
+iface.launch()