diff --git a/OpenSans-Regular.ttf b/OpenSans-Regular.ttf
new file mode 100644
index 0000000..db43334
Binary files /dev/null and b/OpenSans-Regular.ttf differ
diff --git a/merger_FITS.py b/merger_FITS.py
index 7081a59..638f724 100644
--- a/merger_FITS.py
+++ b/merger_FITS.py
@@ -9,7 +9,7 @@ import queue
 import traceback
 
 import tqdm
-from PIL import Image, ImageDraw
+from PIL import Image, ImageDraw, ImageFont
 import numpy as np
 from matplotlib import pyplot as plt
 from astropy.io import fits
@@ -286,6 +286,8 @@ def generate_composite(work_queue, result_queue):
     gammas = [0.375, 0.40, 00.425, 00.45, 00.475, 00.5]
     trimx = 64
     trimy = 100
+    fnt1 = ImageFont.truetype("OpenSans-Regular.ttf", size = 24)
+    fnt2 = ImageFont.truetype("OpenSans-Regular.ttf", size = 16)
     while True:
         try:
             job = work_queue.get()
@@ -293,14 +295,21 @@ def generate_composite(work_queue, result_queue):
                 result_queue.cancel_join_thread()
                 return
             files_this_timestamp, timestamp, processed_images_dir, synthetic_data = job
+            synthetic_filepath = os.path.join(processed_images_dir, f"Composite-{int(timestamp)}_s.jpg")
+            normal_filepath = os.path.join(processed_images_dir, f"Composite-{int(timestamp)}.jpg")
+            filepath = None
             if synthetic_data:
-                filename = f"Composite-{int(timestamp)}_s.jpg"
+                if os.path.isfile(synthetic_filepath):
+                    result_queue.put(("Exists", timestamp))
+                    continue
+                filepath = synthetic_filepath
             else:
-                filename = f"Composite-{int(timestamp)}.jpg"
-            filepath = os.path.join(processed_images_dir, filename)
-            if os.path.isfile(filepath):
-                result_queue.put(("Exists", timestamp))
-                continue
+                if os.path.isfile(synthetic_filepath):
+                    os.remove(synthetic_filepath)
+                if os.path.isfile(normal_filepath):
+                    result_queue.put(("Exists", timestamp))
+                    continue
+                filepath = normal_filepath
 
             base_imgs = []
             for i in range(6):
@@ -402,14 +411,14 @@ def generate_composite(work_queue, result_queue):
 
             img = Image.fromarray((255 * composite_image_data).astype('uint8'))
             timestring = datetime.datetime.fromtimestamp(timestamp, tz = datetime.UTC).strftime('%Y-%m-%d  %H:%M:%S')
-            ImageDraw.Draw(img).text((605, 15), f"NOAA GOES Satellite SUVI Composite - {timestring} UTC",(255,255,255), font_size = 24)
+            ImageDraw.Draw(img).text((602, 15), f"NOAA GOES Satellite SUVI Composite - {timestring} UTC",(255,255,255), font = fnt1)
             for i in range(6): # Draw component angstrom labels
                 if i%2 == 0:
                     xdimtxtoff = 5
                 else:
                     xdimtxtoff = composite_image_data.shape[1] - 44
-                ydimtxtoff = i//2*new_dimy + new_dimy / 2.0 - 6
-                ImageDraw.Draw(img).text((xdimtxtoff, ydimtxtoff), image_names[i], font_size = 16)
+                ydimtxtoff = i//2*new_dimy + new_dimy / 2.0 - 14
+                ImageDraw.Draw(img).text((xdimtxtoff, ydimtxtoff), image_names[i], font = fnt2)
             img.save(filepath, quality = 95)
             result_queue.put(("Created", timestamp))
         
@@ -432,12 +441,12 @@ if __name__ == "__main__":
                         r"..\Data\goes18\l2\data\suvi-l2-ci284\2024",
                         r"..\Data\goes18\l2\data\suvi-l2-ci304\2024",]
     processed_images_dir = r"..\composite\goes18"
-    starttime = time.mktime(datetime.datetime(2024, 1, 1).timetuple())
-    stoptime = time.mktime(datetime.datetime(2025, 1, 1).timetuple())
+    starttime = time.mktime(datetime.datetime(2024, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
+    stoptime = time.mktime(datetime.datetime(2025, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
 
     regex_filename = r"dr_suvi-l2-ci\d{3}_g(16|18)_s\S*\_f.fits$"
     nworkers = 20
-    max_time_gap = 10
+    max_time_gap = 3
 
     file_prefixes = ["dr_suvi-l2-ci" + n[:-1] for n in image_names]
     
@@ -456,6 +465,7 @@ if __name__ == "__main__":
     ncreated = 0
     nexists = 0
     nfailed = 0
+    black_image = Image.fromarray(np.zeros((1080, 1920, 3), dtype='uint8'))
     try:
         files_sorted_by_timestamp = defaultdict(list)
         found_files = 0
@@ -467,11 +477,9 @@ if __name__ == "__main__":
                 for f in files:
                     if filename_tester.match(f):
                         file_parts = f.split("_")
-                        measurement = file_parts[1]
-                        sattelite = file_parts[2]
-                        measure_end_time = datetime.datetime.strptime(file_parts[4][1:16], "%Y%m%dT%H%M%S")
-                        measure_end_time.replace(tzinfo=datetime.timezone.utc)
-                        measure_end_time = int(time.mktime(measure_end_time.timetuple()))
+                        # measurement = file_parts[1]
+                        # sattelite = file_parts[2]
+                        measure_end_time = int(datetime.datetime.strptime(file_parts[4][1:16] + " +0000", "%Y%m%dT%H%M%S %z").timestamp())
                         files_sorted_by_timestamp[measure_end_time].append(os.path.join(root,f))
                         found_files += 1
                     
@@ -531,8 +539,12 @@ if __name__ == "__main__":
                                 synthetic_data = True
                                 files_for_job.append(last_good_files[i])
                             else:
-                                print(f"Detected a gap of {time_gap} frames at {timestamp}, skipping.")
-                                continue
+                                print(f"Detected a gap of {time_gap} frames at {timestamp}, inserting black frames.")
+                                filename = f"Composite-{int(timestamp)}_b.jpg"
+                                filepath = os.path.join(processed_images_dir, filename)
+                                if not os.path.isfile(filepath):
+                                    black_image.save(filepath, quality = 95)
+                                break
                     if len(files_for_job) == 6:
                         work_queue.put((files_for_job, timestamp, processed_images_dir, synthetic_data))
                     else: