Add application file

app.py

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+import sys
+import cv2
+import base64
+import gradio as gr
+import requests
+import numpy as np
+import configparser
+
+
+def run(file):
+    in_image = cv2.imread(file)
+
+    encode_img = cv2.imencode('.jpg', in_image)[1].tostring()
+    encode_img = base64.encodebytes(encode_img)
+    base64_img = str(encode_img, 'utf-8')
+
+    backend_url = os.getenv('BACKEND_URL')
+    url = f'{backend_url}/raster-to-vector-base64'
+    payload = {'image': base64_img}
+    image_request = requests.post(url, json=payload)
+
+    out_img = image_request.json()['image']
+    out_json = image_request.json()['graph']
+
+    decode_img = base64.b64decode(out_img.split(',')[1])
+    decode_img = np.frombuffer(decode_img, dtype=np.uint8)
+    out_img = cv2.imdecode(decode_img, flags=cv2.IMREAD_COLOR)
+
+    return out_img, out_json
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    # Raster-To-Vector on Floor Plan images
+    Please give me star if you like it and reach out to me to get on-premise solutions. (Whatsapp only: +1 442 229 5661)
+    """
+    )
+
+    with gr.TabItem("Floor Plan Recognition"):
+        with gr.Row():
+            with gr.Column():
+                app_input = gr.Image(type='filepath')
+                gr.Examples(['images/1.jpg', 'images/2.png', 'images/3.png', 'images/4.png'],
+                            inputs=app_input)
+                start_button = gr.Button("Run")
+            with gr.Column():
+                app_output = [gr.Image(type="numpy"), gr.JSON()]
+
+        start_button.click(run, inputs=app_input, outputs=app_output)
+
+
+demo.launch()

requirements.txt

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+opencv-python==4.8.0.74