edit path

app.py

@@ -5,6 +5,7 @@ from utils_func import create_dir, main_processing
 
 create_dir("tempDir")
 
+
 def load_image(image_file):
 	img = Image.open(image_file)
 	return img
@@ -36,7 +37,7 @@ def streamlit_app():
         col1, col2, col3 = st.columns(3)
         with col1:
             st.image(image, caption="Image before processing")
-        save_path = "tempDir\\"+ image_file.name
+        save_path = "tempDir/"+ image_file.name
         image.save(save_path)
 
 
@@ -64,7 +65,7 @@ def streamlit_app():
                                 st.write('\n')
                                 st.write('\n')
 
-                                file_name = final_img_path.split("\\")[-1].split(".")[-2]
+                                file_name = save_path.split("/")[-1].split(".")[-2] +"_from_abc" + ".png"
                                 if st.download_button(
                                     label="Download postprocessing image",
                                     data=file,
@@ -80,12 +81,12 @@ if __name__ == '__main__':
     tf.random.set_seed(42)
 
     bg_path = ""
-    background_model_path = "weight_files\\model.h5"
-    detection_model_path = "weight_files\\clothes_detection_model.pt"
+    background_model_path = "weight_files/model.h5"
+    detection_model_path = "weight_files/clothes_detection_model.pt"
 
-    stadium_sport_bg_path = "backgrounds\\camnou_stadium.jpg"
-    beach_swim_bg_path = "backgrounds\\beach.jpg"
-    office_bg_path = "backgrounds\\office-bg.jpg"
+    stadium_sport_bg_path = "backgrounds/camnou_stadium.jpg"
+    beach_swim_bg_path = "backgrounds/beach.jpg"
+    office_bg_path = "backgrounds/office-bg.jpg"
 
     image_path = None
 

metrics.py

@@ -1,5 +1,8 @@
 from libs import *
 
+smooth = 1e-15
+
+
 def iou(y_true, y_pred):
     def f(y_true, y_pred):
         intersection = (y_true * y_pred).sum()
@@ -9,12 +12,14 @@ def iou(y_true, y_pred):
         return x
     return tf.numpy_function(f, [y_true, y_pred], tf.float32)
 
-smooth = 1e-15
+
+
 def dice_coef(y_true, y_pred):
     y_true = tf.keras.layers.Flatten()(y_true)
     y_pred = tf.keras.layers.Flatten()(y_pred)
     intersection = tf.reduce_sum(y_true * y_pred)
     return (2. * intersection + smooth) / (tf.reduce_sum(y_true) + tf.reduce_sum(y_pred) + smooth)
 
+
 def dice_loss(y_true, y_pred):
     return 1.0 - dice_coef(y_true, y_pred)

utils_func.py

@@ -36,7 +36,7 @@ def choose_background(col1, col2, col3):
 
         bg_image = load_image(background_file)
         print(type(bg_image))
-        save_path = "backgrounds\\" + background_file.name
+        save_path = "backgrounds/" + background_file.name
         bg_image.save(save_path)
 
         return bg_image, save_path