init app

app.py

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+import base64
+import os
+import gradio as gr
+import openai
+
+# OpenAI API Key
+api_key = os.getenv("OPENAI_API_KEY")
+client = openai.Client(api_key=api_key)
+
+# Function to encode the image
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode("utf-8")
+
+
+def ask_openai_about_image(image_path, user_question):
+    base64_image = encode_image(image_path)
+    messages = [
+        {
+            "role": "system",
+            "content": "You are an automotive expert. Your job is to identify details in a given photo of a car.",
+        },
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": user_question},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
+                },
+            ],
+        },
+    ]
+
+    response = client.chat.completions.create(model="gpt-4o", messages=messages)
+    return response.choices[0].message.content
+
+
+# Gradio interface
+iface = gr.Interface(
+    fn=ask_openai_about_image,
+    inputs=[
+        gr.Image(label="Upload Image of Car", type="filepath"),
+        gr.Textbox(label="Ask if a specific badge is present"),
+    ],
+    examples=[
+        ["data/peugeot_206_rear.jpg", "Does this car have the badge 206?"],
+        ["data/peugeot_306_rear.jpg", "Does this car have the badge 106?"],
+    ],
+    outputs="text",
+    title="Badge Detector",
+    description="Upload an image of a car and type your question about the car. You can also select an example image from our dataset.",
+)
+
+iface.launch()

requirements.txt

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+gradio
+openai