added model

app.py

@@ -1,7 +1,34 @@
 import gradio as gr
+import tensorflow as tf
 
-def greet(name):
-    return "Hello " + name + "!!"
+# def greet(name):
+#     return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def predict_image(image):
+    # Preprocess the image
+    image = image.reshape((1, 160, 160, 3))
+
+    model = tf.keras.models.load_model('./cat_dog_recognition.h5')
+
+    # Make prediction
+    pred = model.predict(image)
+
+    predicted_label = "Dog " + str(pred[0])
+    if pred >= 0.5:
+        predicted_label = "Cat " + str(pred[0])
+
+    # Return the predicted label
+    return f"Predicted Label: {predicted_label}"
+
+
+
+# input_image = [gr.components.Image(type="filepath" , label="Input Image"),]
+
+# iface = gr.Interface(fn=detect, inputs=input_image, outputs="text" , title="Cat vs Dog Detector")
+# iface.launch()
+
+image_input = gr.inputs.Image(shape=(160,160))
+label_output = gr.outputs.Textbox()
+
+# Create the Gradio interface
+gr.Interface(fn=predict_image, inputs=image_input, outputs=label_output).launch()

cat_dog_recognition.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e521bd487a0f1c3e98fe0b0b36fd676e5f442dfed747780425e86b3fc3649067
+size 250489304