Upload app.py

app.py

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+import gradio as gr
+
+from tools.extract_features import extract_features_image
+from tools.search import search_similar_products
+from tools.load_database import select_database
+
+# Default values
+MARCAS = ["Ninguno", "Zara", "Adidas", "Nike", "Puma", "Levi's", "Forever 21", "H&M", "Gap", "Converse", "Mango"]
+PRENDAS = ["bag", "dress", "hat", "jacket", "pants", "shirt", "shoe", "shorts", "skirt", "sunglass"]
+
+
+def process_image(image, marca, prenda):
+   """Visual Search Pipeline"""
+   vgg_search = extract_features_image(image)
+   database = select_database(marca, prenda)
+   result = search_similar_products(vgg_search, database)
+   return result
+
+
+# Gradio app
+examples = [
+    ["examples/bag_93.99.png", "Adidas", "bag"],
+    ["examples/shirt_82.84.png", "Nike", "shirt"],
+    ["examples/skirt_87.54.png", "Puma", "skirt"]
+]
+
+title =  "Visual Search 🔍 | Powered by Xpertium SA"
+description =  """
+               <p style='text-align: center'>Carga tu imagen y selecciona la marca & tipo de prenda.</p>
+               """
+
+iface = gr.Interface(
+  fn=process_image, 
+  inputs=[
+     gr.Image(label="imagen"), 
+     gr.Dropdown(label="marca", choices=MARCAS, value=MARCAS[1]),
+     gr.Dropdown(label="prenda", choices=PRENDAS, value=PRENDAS[1]),
+     ], 
+  outputs=gr.JSON(label="resultado"),
+  title=title,
+  examples=examples,
+  description=description
+)
+
+iface.launch()