update postprocessing

animationPipeline.py

@@ -5,8 +5,15 @@ from AnimationTransformer import predict
 import torch.nn as torch
 import torch
 import pandas as pd
-
-def animateLogo(path : str):
+import shutil
+
+def animateLogo(path : str, targetPath : str):
+    try:
+        # Copy the original file to the new location with the new filename
+        shutil.copyfile(path, targetPath)
+        print(f"File copied and renamed to {targetPath}")
+    except Exception as e:
+        print(f"An error occurred: {e}")
     #transformer
     NUM_HEADS = 6 # Dividers of 282: {1, 2, 3, 6, 47, 94, 141, 282}
     NUM_ENCODER_LAYERS = 2
@@ -44,7 +51,7 @@ def animateLogo(path : str):
     result = pd.DataFrame({"model_output" : [row.tolist() for index, row in result.iterrows()]})
     result["animation_id"] = range(len(result))
     print(result, path)
-    animate_logo(result, path)
+    animate_logo(result, targetPath)
 
 #logo = "data/examples/logo_181.svg"
 #animateLogo(logo)

app.py

@@ -21,5 +21,5 @@ if uploaded_file is not None:
       sys.setrecursionlimit(1500)
       animateLogo(path)
       with open(path, "rb") as file:
-        st.download_button('Download animated SVG', data=file, file_name=uploaded_file.name+"_animated.svg")
+        st.download_button('Download animated SVG', data=file, file_name=uploaded_file.name[:-3]+"_animated.svg")
     

src/postprocessing/postprocessing.py

@@ -15,6 +15,16 @@ random.seed(0)
 filter_id = 0
 
 def animate_logo(model_output: pd.DataFrame, logo_path: str):
+    # Add animation id
+    document = minidom.parse(logo_path)
+
+    paths = document.getElementsByTagName('path')
+    for i in range(len(paths)):
+        paths[i].setAttribute('animation_id', str(i))
+    with open(path, 'wb') as svg_file:
+        svg_file.write(document.toxml(encoding='iso-8859-1'))
+
+    
     logo_xmin, logo_xmax, logo_ymin, logo_ymax = get_svg_bbox(logo_path)
     # ---- Normalize model output ----
     animations_by_id = defaultdict(list)