Update app.py

app.py

@@ -1,9 +1,16 @@
 import time
 import cv2
+import numpy as np
 import gradio as gr
+from PIL import Image
 
 index = 1
 
+def process(dress):
+    # Dummy processing function for demonstration
+    # Replace with your actual processing logic
+    return cv2.GaussianBlur(dress, (15, 15), 0)
+
 def mainTest(inputpath, outpath):
     watermark = deep_nude_process(inputpath)
     watermark1 = cv2.cvtColor(watermark, cv2.COLOR_BGRA2RGBA)
@@ -20,16 +27,17 @@ def deep_nude_process(inputpath):
 
 def inference(img):
     global index
+    img = np.array(img)  # Convert PIL image to NumPy array
     bgra = cv2.cvtColor(img, cv2.COLOR_RGBA2BGRA)
-    inputpath = "input_" + str(index) + ".jpg"
+    inputpath = f"input_{index}.jpg"
     cv2.imwrite(inputpath, bgra)
 
-    outputpath = "out_" + str(index) + ".jpg"
+    outputpath = f"out_{index}.jpg"
     index += 1
     print(time.strftime("START!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime()))
     output = mainTest(inputpath, outputpath)
     print(time.strftime("Finish!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime()))
-    return output
+    return Image.fromarray(output)
 
 title = "Undress AI"
 description = "⛔ Input photos of people, similar to the test picture at the bottom, and undress pictures will be produced. You may have to wait 30 seconds for a picture. 🔞 Do not upload personal photos 🔞 There is a queue system. According to the logic of first come, first served, only one picture will be made at a time. Must be able to at least see the outline of a human body ⛔"