Fix Bugs

app.py

@@ -8,52 +8,54 @@ import cv2
 
 from autodistill.core.custom_detection_model import CustomDetectionModel
 
+# Hardcoded values - ensure to protect the API key
+api_key = "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"
+dino_prompt = "buildings . parks ."
+gpt_prompt = "carbon sinks"
+
 MARKDOWN = """
 # NESGPT-AutoAnnotator
 Grounding DINO for Zero-Shot Carbon Sink Identification and Object Segmentation
 ."""
 
-def respond(api_key, input_image, dino_prompt, gpt_prompt):
+def respond(input_image):
     input_image = cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
-    cv2.imwrite("input.jpg", input_image)
-
-    DINOGPT = CustomDetectionModel(
-        detection_model=GroundingDINO(
-            CaptionOntology({dino_prompt: dino_prompt})
-        ),
-        classification_model=GPT4V(
-            CaptionOntology({k: k for k in gpt_prompt.split(", ")}),
-            api_key=api_key
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
+        cv2.imwrite(temp_file.name, input_image)
+
+        DINOGPT = CustomDetectionModel(
+            detection_model=GroundingDINO(
+                CaptionOntology({dino_prompt: dino_prompt})
+            ),
+            classification_model=GPT4V(
+                CaptionOntology({k: k for k in gpt_prompt.split(", ")}),
+                api_key=api_key  # Use the hardcoded API key
+            )
         )
-    )
 
-    results = DINOGPT.predict("input.jpg")
+        results = DINOGPT.predict(temp_file.name)
 
-    result = plot(
-        image=cv2.imread("input.jpg"),
-        detections=results,
-        classes=gpt_prompt.split(", "),
-        raw=True
-    )
+        result_image = plot(
+            image=cv2.imread(temp_file.name),
+            detections=results,
+            classes=gpt_prompt.split(", "),
+            raw=True
+        )
 
-    return result
+    return result_image
 
 with gr.Blocks() as demo:
     gr.Markdown(MARKDOWN)
     with gr.Row():
         with gr.Column():
-            api_key_textbox = gr.Textbox(
-                label="OpenAI API KEY", type="password")
-            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="Carbon Sink Identifier")
-            submit_button = gr.Button()
+            submit_button = gr.Button("Identify Carbon Sinks")
 
     submit_button.click(
         fn=respond,
-        inputs=[api_key_textbox, input_image, dino_prompt, gpt_prompt],
+        inputs=[input_image],
         outputs=[output_image]
     )