fix: GIF image conversion issue #38

app/modules/decimermodules.py

@@ -1,20 +1,64 @@
 import os
 import cv2
+from PIL import Image
 from decimer_segmentation import segment_chemical_structures_from_file
 from DECIMER import predict_SMILES
 
 
-def getPredictedSegments(path: str):
-    """Takes an image filepath and returns a set of paths of segmented images
+def convert_image(path: str):
+    """Takes an image filepath of GIF image and returns Hi Res PNG image.
     Args:
-        input_path (str): path of an image
+        input_path (str): path of an image.
 
     Returns:
         segment_paths (list): a list of paths of segmented images.
     """
-    smiles_predicted = []
+    img = Image.open(path).convert("RGBA")
+    new_size = int((float(img.width) * 2)), int((float(img.height) * 2))
+    resized_image = img.resize(new_size, resample=Image.LANCZOS)
+    background_size = int((float(resized_image.width) * 2)), int(
+        (float(resized_image.height) * 2)
+    )
+    new_im = Image.new(resized_image.mode, background_size, "white")
+    paste_pos = (
+        int((new_im.size[0] - resized_image.size[0]) / 2),
+        int((new_im.size[1] - resized_image.size[1]) / 2),
+    )
+    new_im.paste(resized_image, paste_pos)
+    new_im.save(path.replace("gif", "png"), optimize=True, quality=100)
+    return path.replace("gif", "png")
+
+
+def get_segments(path: str):
+    """Takes an image filepath and returns a set of paths and image name of segmented images.
+    Args:
+        input_path (str): path of an image.
+
+    Returns:
+        image_name (str): image file name.
+        segments (list): a set of segmented images.
+    """
     image_name = os.path.split(path)[1]
-    segments = segment_chemical_structures_from_file(path)
+    if image_name[-3:].lower() == "gif":
+        new_path = convert_image(path)
+        segments = segment_chemical_structures_from_file(new_path)
+        return image_name, segments
+    else:
+        segments = segment_chemical_structures_from_file(path)
+        return image_name, segments
+
+
+def getPredictedSegments(path: str):
+    """Takes an image filepath and returns predicted SMILES for segmented images.
+    Args:
+        input_path (str): path of an image.
+
+    Returns:
+        predictions (list): a list of SMILES of the segmented images.
+    """
+    smiles_predicted = []
+    image_name, segments = get_segments(path)
+
     if len(segments) == 0:
         smiles = predict_SMILES(path)
         return smiles