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app.py

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+import gradio as gr
+import requests
+from io import BytesIO
+import base64
+import matplotlib.image as mpimg
+import cv2
+
+def string_to_img(base64_string):
+    imgdata = base64.b64decode(base64_string + '==')
+    im = BytesIO(imgdata)
+    img = mpimg.imread(im, format='PNG')
+    opencv_img= cv2.cvtColor(np.array(img), cv2.COLOR_BGR2RGB)
+    return opencv_img
+
+def img_to_string(img):
+    _, encoded_img = cv2.imencode('.PNG', img)
+    base64_string = base64.b64encode(encoded_img).decode('utf-8')
+    return base64_string
+
+def api_image_processing(image):
+    # API Endpoint
+    url = "http://18.132.59.76/fmc_api"
+    # Step 1
+    b64_string = img_to_string(image)
+    #  Step 2
+    payload ={"base64_string": b64_string}
+    base64_string_resp = requests.post(url=url, data=payload) 
+    # Step 3
+    img_output = string_to_img(base64_string_resp)
+    # Return processed image
+    return img_output
+
+demo = gr.Interface(
+    api_image_processing, 
+    gr.Image(source="webcam", streaming=True), 
+    "image",
+    live=True
+)
+
+demo.launch(share=True, debug=True)

requirements.txt

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+Flask==2.0.1
+gradio==3.16.2
+ipython==8.8.0
+matplotlib==3.6.2
+mediapipe==0.9.0.1
+numpy==1.21.5
+opencv_contrib_python==4.7.0.68
+requests==2.28.1