add garment type

app.py

@@ -34,6 +34,8 @@ features = "Brand: Duckly. \nProduct name: Duck runner pro. \nKey properties: t-
 
 reference = " "
 
+garment_type = "all"
+
 import base64
 import requests
 
@@ -59,13 +61,15 @@ def get_json(text: str):
     return json.loads(text)
 
 
-def detect_features(image_paths):
+def detect_features(image_paths, garment_type):
     # Path to your image
     # image_path = "path_to_your_image.jpg"
 
     # Getting the base64 string
     try:
         base64_images = [encode_image(image_path[0]) for image_path in image_paths]
+        if garment_type == "" or garment_type == "all":
+            garment_type = "garment"
     
         headers = {
         "Content-Type": "application/json",
@@ -80,8 +84,8 @@ def detect_features(image_paths):
             "content": [
                 {
                 "type": "text",
-                "text": """Describe the features of the garment in the photos in less than 100 words.
-                What is the intended use of the garment in this image, use at most 5 words for intended use?
+                "text": """Describe the features of the {garment_type} in the photos in less than 100 words.
+                What is the intended use of the {garment_type} in this image, use at most 5 words for intended use?
                 Generate alt text for each of the images.
                 If the photo does not contain a garment, return 'No garment detected'.
                 If the photo contains a garment, return the result in in the following JSON format without any preceding or trailing text: 
@@ -115,9 +119,9 @@ def detect_features(image_paths):
         return "", []
 
 
-def generate(features, image, structure, reference, model, temperature):
+def generate(features, image, garment_type, structure, reference, model, temperature):
     print(f"features {features},\n image {image},\n structure{structure},\n model{model},\n temperature {temperature},\n reference {reference}")
-    image_features, base64_images = detect_features(image)
+    image_features, base64_images = detect_features(image, garment_type)
     detected_features = ""
     intended_use = ""
     alt_texts = []
@@ -149,6 +153,7 @@ demo = gr.Interface(
     fn=generate,
     inputs=[gr.Textbox(features, label="Features"), 
             gr.Gallery(label="Product image(s)", type="filepath"), 
+            gr.Textbox(garment_type, label="Garment type"),
             gr.Textbox(structure, label="Structure"), 
             gr.Textbox(reference, label="Reference copy"),
             gr.Dropdown(["gpt-4-turbo", "gpt-3.5-turbo", "claude-3-sonnet-20240229", "claude-3-opus-20240229", "llama3-70b-8192"], value="llama3-70b-8192", label="Model"),