use numpy

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
-import requests
+import io, requests
+import matplotlib.pyplot as plt
 
 # def abnormal(image):
 #     if (image is None) or (image == ''):
@@ -35,15 +36,16 @@ import requests
 
 def abnormal_stream(image):
     try:
-        with open(image, 'rb') as f:
-            r = requests.post(
-                'https://6a051cv20250210-prediction.cognitiveservices.azure.com/customvision/v3.0/Prediction/29f565b7-4710-47a5-8a47-723048ff7ec9/classify/iterations/Iteration2/image',
-                headers={
-                    'Prediction-Key': '8uyKSiqRNbG2JLdMjI8AeOzADtORP3jRh5klqQr0JsJrBBt7x7iPJQQJ99BBACYeBjFXJ3w3AAAIACOGHg4K',
-                    'Content-Type': 'application/octet-stream',
-                },
-                data=f.read(),
-            )
+        buf = io.BytesIO()
+        plt.imsave(buf, image, format='png')
+        r = requests.post(
+            'https://6a051cv20250210-prediction.cognitiveservices.azure.com/customvision/v3.0/Prediction/29f565b7-4710-47a5-8a47-723048ff7ec9/classify/iterations/Iteration2/image',
+            headers={
+                'Prediction-Key': '8uyKSiqRNbG2JLdMjI8AeOzADtORP3jRh5klqQr0JsJrBBt7x7iPJQQJ99BBACYeBjFXJ3w3AAAIACOGHg4K',
+                'Content-Type': 'application/octet-stream',
+            },
+            data=buf.getvalue(),
+        )
 
         if r.status_code != 200:
             return {'확인불가': 1.0, r.status_code: 0.0, r.text: 0.0}
@@ -63,7 +65,7 @@ def abnormal_stream(image):
 with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
-            input_img = gr.Image(sources=["webcam"], type="filepath")
+            input_img = gr.Image(sources=["webcam"])
         with gr.Column():
             output_label = gr.Label()
         dep = input_img.stream(abnormal_stream, [input_img], [output_label])