create care label demo app

app.py

@@ -0,0 +1,48 @@
+import io
+import base64
+import os
+
+import requests
+from PIL import Image
+
+import numpy as np
+import gradio as gr
+
+
+def image_to_base64(image):
+    if isinstance(image, np.ndarray):
+        image = Image.fromarray(image)
+
+    buffered = io.BytesIO()
+    image.save(buffered, format="JPEG")
+    img_str = base64.b64encode(buffered.getvalue()).decode()
+
+    return f"data:image/jpeg;base64,{img_str}"
+
+
+def process_image(image: Image.Image):
+    base64_url = image_to_base64(image)
+    api_hostname = os.getenv('CARE_LABEL_API', 'http://0.0.0.0:8000')
+    response = requests.post(
+        url=f'{api_hostname}/v1/care-label/extract-info',
+        json={
+            "imageUrl": base64_url
+        }
+    )
+    json_response = response.json()
+    for key, value in json_response.items():
+        if isinstance(value, str):
+            json_response[key] = value.replace('\n', '<br>')
+    return json_response
+
+
+iface = gr.Interface(
+    fn=process_image,
+    inputs="image",
+    outputs="json",
+    title='Care Label - Information Extraction',
+    description='The demo to extract care instruction from care label image.',
+    allow_flagging='never',
+
+)
+iface.launch()

requirements.txt

@@ -0,0 +1,3 @@
+numpy
+gradio
+pillow