rollback

app.py

@@ -1,19 +1,6 @@
 import gradio as gr
 import requests
 from io import BytesIO
-from azure.cognitiveservices.vision.customvision.prediction import CustomVisionPredictionClient
-from msrest.authentication import ApiKeyCredentials
-
-classification_prediction_endpoint = "https://6b034cv20250210-prediction.cognitiveservices.azure.com/"
-classification_prediction_key = "EAqbiKHt9sYSwFiO7U1NUBngdvnBoJRmd3ZLl0V0XzKkBbzibzPoJQQJ99BBACYeBjFXJ3w3AAAIACOGYNGQ"
-classification_project_id = "b632b81b-f8d4-48ed-a74d-022aab130c5d"
-classification_publish_iteration_name = "Iteration4"
-
-classification_credentials = ApiKeyCredentials(in_headers={"Prediction-key": classification_prediction_key})
-classification_predictor = CustomVisionPredictionClient(
-    endpoint=classification_prediction_endpoint, 
-    credentials=classification_credentials
-)
 
 def abnormal_stream(image):
     try:
@@ -21,15 +8,18 @@ def abnormal_stream(image):
         image.save(byte_io, 'png')
         byte_io.seek(0)
 
-        r = classification_predictor.classify_image(
-            classification_project_id,
-            classification_publish_iteration_name,
-            byte_io,
+        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=byte_io,
         )
 
-        if not r.predictions:
+        if r.status_code != 200:
             return {'확인불가': 1.0, r.status_code: 0.0, r.text: 0.0}, None
-        return str(r.predictions), output_audio
+
         output_dict = {}
 
         for item in r.json()['predictions']:
@@ -53,7 +43,7 @@ with gr.Blocks(
         with gr.Column():
             input_img = gr.Image(sources=["webcam"], type="pil")
         with gr.Column():
-            output_label = gr.Text()
+            output_label = gr.Label()
             output_audio = gr.Audio(autoplay=True)
         dep = input_img.stream(abnormal_stream, [input_img], [output_label, output_audio])
 

requirements.txt

@@ -1 +0,0 @@
-azure-cognitiveservices-vision-customvision