rollback

app.py

@@ -1,6 +1,5 @@
 import gradio as gr
-import io, requests
-import matplotlib.pyplot as plt
+import requests
 
 # def abnormal(image):
 #     if (image is None) or (image == ''):
@@ -36,16 +35,15 @@ import matplotlib.pyplot as plt
 
 def abnormal_stream(image):
     try:
-        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(),
-        )
+        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(),
+            )
 
         if r.status_code != 200:
             return {'확인불가': 1.0, r.status_code: 0.0, r.text: 0.0}
@@ -65,7 +63,7 @@ def abnormal_stream(image):
 with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
-            input_img = gr.Image(sources=["webcam"])
+            input_img = gr.Image(sources=["webcam"], type="filepath")
         with gr.Column():
             output_label = gr.Label()
         dep = input_img.stream(abnormal_stream, [input_img], [output_label])