updated segmentation utils and app

app.py

@@ -16,6 +16,7 @@ def segment_gradio_image(api_token, model, image):
             'red'
         )
         segments_list = "No segments available."
+        return api_token_message, text_image, segments_list
     else:
         if image is None:
             text_image = print_text_on_image_centered(
@@ -24,6 +25,7 @@ def segment_gradio_image(api_token, model, image):
                 'orange'
             )
             segments_list = "No segments available."
+            return api_token_message, text_image, segments_list
         else:
             text_image = print_text_on_image_centered(
                 create_background_image(500, 500, "white"),

segmentation_utils.py

@@ -2,7 +2,6 @@ import requests
 from pycocotools import mask
 import matplotlib.pyplot as plt
 from PIL import Image, ImageDraw, ImageOps, ImageFont
-from dotenv import find_dotenv, load_dotenv
 import os
 import base64
 import io
@@ -15,11 +14,7 @@ import traceback
 from pprint import pprint
 
 
-load_dotenv(find_dotenv())
-HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 
-API_URL = "https://api-inference.huggingface.co/models/facebook/mask2former-swin-tiny-coco-panoptic"
-headers = {"Authorization": f"Bearer {HUGGINGFACEHUB_API_TOKEN}"}
 
 # Función para transformar la entrada en un array de numpy
 # Si la entrada es una URL, descarga la imagen y la convierte en un array de numpy
@@ -89,7 +84,12 @@ def transform_image_to_numpy_array2(input):
     else:
         raise ValueError("La entrada no es un array de numpy, una URL ni una ruta de archivo.")
     
-def segment_image_from_numpy(image_array):
+def segment_image_from_numpy(image_array, api_token, model):
+    
+    #API_URL = "https://api-inference.huggingface.co/models/facebook/mask2former-swin-tiny-coco-panoptic"
+    API_URL = f"https://api-inference.huggingface.co/models/facebook/{model}"
+    headers = {"Authorization": f"Bearer {api_token}"}
+
     # Convert the image to bytes
     is_success, im_buf_arr = cv2.imencode(".jpg", image_array)
     data = im_buf_arr.tobytes()
@@ -340,7 +340,7 @@ def segment_and_overlay_results(image_path, api_token, model):
        #     return None, []
         
         ic("--- calling segment_image_from_path ---")    
-        segments = segment_image_from_numpy(image)
+        segments = segment_image_from_numpy(image, api_token, model)
         #if image_type == 'FILE':
         #    segments = segment_image_from_path(image_path)
         #if image_type == 'NUMPY ARRAY':