feat(ml): improve the inference for any paths.txt and longer frames

scripts/gen_vid_diffusion.py

@@ -52,6 +52,14 @@
 from util.util import flatten_json
 
 
+def atoi(text):
+    return int(text) if text.isdigit() else text
+
+
+def natural_keys(text):
+    return [atoi(c) for c in re.split("(\d+)", text)]
+
+
 def load_model(
     model_in_dir,
     model_in_filename,
@@ -237,14 +245,25 @@ def generate(
     for i, delta_values in enumerate(mask_delta):
         if len(delta_values) == 1:
             mask_delta[i].append(delta_values[0])
-
     # Load image
     with open(args.paths_file, "r") as file:
         lines = file.readlines()
-
-    image_bbox_pair = [
-        line.strip().split() for line in lines[: opt.data_temporal_number_frames]
+    paths_img = []
+    paths_bbox = []
+
+    image_bbox_pairs = []
+    for line in lines:
+        parts = line.strip().split()
+        image_bbox_pairs.append((parts[0], parts[1]))
+
+    image_bbox_pairs.sort(key=lambda x: natural_keys(x[0]))
+    startframe = random.randint(100, 10000)
+    limited_image_bbox_pairs = image_bbox_pairs[
+        startframe : startframe + opt.data_temporal_number_frames + 10
     ]
+    limited_paths_img = [pair[0] for pair in limited_image_bbox_pairs]
+    limited_paths_bbox = [pair[1] for pair in limited_image_bbox_pairs]
+
     cond_image_list = []
     y_t_list = []
     y0_tensor_list = []
@@ -254,7 +273,7 @@ def generate(
     img_tensor_list = []
     out_img_list = []
 
-    for img_path, bbox_path in image_bbox_pair:
+    for img_path, bbox_path in zip(limited_paths_img, limited_paths_bbox):
         img_in = os.path.join(args.data_root, img_path)
         maskin = os.path.join(args.data_root, bbox_path)
         bbox_select = None