Update App.Py

app.py

@@ -9,12 +9,9 @@ import cv2
 from autodistill.core.custom_detection_model import CustomDetectionModel
 
 MARKDOWN = """
-# DINO-GPT4V
-
-Use Grounding DINO and GPT-4V to label specific objects.
-
-Visit [awesome-openai-vision-api-experiments](https://github.com/roboflow/awesome-openai-vision-api-experiments) 
-repository to find more OpenAI Vision API experiments or contribute your own."""
+# NESGPT-AutoAnnotator
+Grounding DINO for Zero-Shot Carbon Sink Identification and Object Segmentation
+."""
 
 def respond(api_key, input_image, dino_prompt, gpt_prompt):
     input_image = cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
@@ -47,11 +44,11 @@ with gr.Blocks() as demo:
         with gr.Column():
             api_key_textbox = gr.Textbox(
                 label="OpenAI API KEY", type="password")
-            dino_prompt = gr.Textbox(label="Grounding DINO Prompt")
-            gpt_prompt = gr.Textbox(label="GPT-4V Prompt")
-            input_image = gr.Image(type="numpy", label="Input Image")
+            dino_prompt = buildings . parks .
+            gpt_prompt = carbon sinks
+            input_image = gr.Image(type="numpy", label="Input Location")
         with gr.Column():
-            output_image = gr.Image(type="numpy", label="Output Image")
+            output_image = gr.Image(type="numpy", label="Carbon Sink Identifier")
             submit_button = gr.Button()
 
     submit_button.click(