added labels

app.py

@@ -5,7 +5,6 @@ from pprint import pprint
 import gradio as gr
 import os
 
-
 API_KEY = os.environ.get('PLANT_API_KEY')  # Your API_KEY from https://my.plantnet.org/account/settings
 PROJECT = "all";  # try specific floras: "weurope", "canada"
 api_endpoint = f"https://my-api.plantnet.org/v2/identify/{PROJECT}?api-key={API_KEY}&lang=zh"
@@ -15,37 +14,33 @@ def identify_plant(image_paths, organs):
     for image_path in image_paths:
         image_data = open(image_path, 'rb')
         files.append(('images', (image_path, image_data)))
-
     data = {'organs': organs}
     req = requests.Request('POST', url=api_endpoint, files=files, data=data)
     prepared = req.prepare()
-
     s = requests.Session()
     response = s.send(prepared)
     json_result = json.loads(response.text)
-
     # Close the opened files
     for _, (_, image_data) in files:
         image_data.close()
-
     return response.status_code, json_result
 
-
-def gradio_interface(files, organs):
-    image_paths = [file.name for file in files]
+def gradio_interface(image_path, organs):
+    image_paths = [image_path]
     print(image_paths)
     status_code, json_result = identify_plant(image_paths, organs)
-    
     return json_result.get("bestMatch",None), json_result
+
 with gr.Blocks() as demo:
-    file_output = gr.File()
-    upload_button = gr.UploadButton("Click to Upload a File", file_types=["image", "video"], file_count="multiple")
-    organs_input = gr.CheckboxGroup(choices=["flower", "leaf", "fruit", "bark", "habit"])
-    best_match_text = gr.Textbox()
-    json_text = gr.JSON()
-    upload_button.upload(gradio_interface, inputs=[upload_button,organs_input], outputs = [best_match_text,json_text])
+    image = gr.Image(type="filepath", label = "Plant Image")
+    identify_btn = gr.Button("Identify")
+    
+    organs_input = gr.CheckboxGroup(choices=["flower", "leaf", "fruit", "bark", "habit"],label="Organs", info="What are the organs?")
+    best_match_text = gr.Textbox(label="Scientific Name")
+    json_text = gr.JSON(label="Raw Json String")
+    
+    identify_btn.click(gradio_interface, inputs=[image,organs_input], outputs = [best_match_text,json_text])
 
-#gr.Interface(fn=gradio_interface, inputs=[image_input, organs_input], outputs=outputs).launch()
 demo.launch()