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.env

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+  
+PredictionEndpoint=https://iti109sectiona-prediction.cognitiveservices.azure.com/
+PredictionKey=2R51EjhFY9DBGDZfvD3M7LFZbmF1OgqquIVyOh9dJAJbrPpIUQAZJQQJ99ALACqBBLyXJ3w3AAAIACOGYTID
+ProjectID=6c578dc2-4535-4143-b9b7-a6508ff90b85
+ModelName=fruit-classifier

app.py

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+from azure.cognitiveservices.vision.customvision.prediction import CustomVisionPredictionClient
+from msrest.authentication import ApiKeyCredentials
+from dotenv import load_dotenv
+from PIL import Image
+import os
+import gradio as gr
+from io import BytesIO
+
+#global prediction_endpoint
+#global prediction_key
+#global project_id
+#global model_name
+
+ # Get Configuration Settings
+load_dotenv()
+prediction_endpoint = os.getenv('PredictionEndpoint')
+prediction_key = os.getenv('PredictionKey')
+project_id = os.getenv('ProjectID')
+model_name = os.getenv('ModelName')
+
+def classifyImage(image):
+   
+    try:
+        # Convert PIL Image to bytes
+        image_bytes = BytesIO()
+        image.save(image_bytes, format='JPEG')
+        image_bytes = image_bytes.getvalue()
+
+        # Authenticate a client for the training API
+        credentials = ApiKeyCredentials(in_headers={"Prediction-key": prediction_key})
+        prediction_client = CustomVisionPredictionClient(endpoint=prediction_endpoint, credentials=credentials)
+
+        # Classify test images
+        results = prediction_client.classify_image(project_id, model_name, image_bytes)
+
+        # Loop over each label prediction and print any with probability > 50%
+        for prediction in results.predictions:
+            if prediction.probability > 0.5:
+                summary = ('{} ({:.0%})'.format(prediction.tag_name, prediction.probability))
+                return summary
+    except Exception as ex:
+        return None, f"Error: {str(ex)}"
+
+title = "Detect 3 types of fruits - Carrot, Cucumber, Pear"
+interface = gr.Interface(
+                fn=classifyImage,
+                inputs=gr.Image(type="pil", label="Input Image"),
+                outputs=gr.Textbox(label="Object detection confidence level"),
+                title=title,
+             )
+
+# Launch the interface
+interface.launch(share=True)
+

requirements.txt

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+azure-cognitiveservices-vision-customvision
+msrest
+huggingface_hub
+gradio
+pillow