Update app.py

app.py

@@ -109,11 +109,19 @@ def normalize_and_save_video(input_video_path, output_video_path):
     print(f"NORMALIZE DONE!")
     return output_video_path
 
-    
+def make_nearest_multiple_of_32(number):
+    remainder = number % 32
+    if remainder <= 16:
+        number -= remainder
+    else:
+        number += 32 - remainder
+    return number 
 
 def run_inference(prompt, video_path, condition, video_length, seed, steps):
     
     seed = math.floor(seed)
+    o_width = get_video_dimension(video_path)[0]
+    o_height = get_video_dimension(video_path)[1]
     
     # Get FPS of original video input
     target_fps = get_video_dimension(video_path)[2] 
@@ -126,7 +134,9 @@ def run_inference(prompt, video_path, condition, video_length, seed, steps):
     total_frames = get_video_dimension(video_path)[3]
 
     # Resize the video
-    #resized = resize_video(video_path, 'resized.mp4', 512, 512, target_fps)
+    r_width = make_nearest_multiple_of_32(o_width)
+    r_height = make_nearest_multiple_of_32(o_height)
+    resized = resize_video(video_path, 'resized.mp4', r_width, r_height, target_fps)
 
     # normalize pixels
     #normalized = normalize_and_save_video(resized, 'normalized.mp4')
@@ -141,9 +151,9 @@ def run_inference(prompt, video_path, condition, video_length, seed, steps):
 
     print(f"RUNNING INFERENCE ...")
     if video_length > 12:
-        command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --temp_chunk_path 'result' --width 512 --height 512 --fps {target_fps} --seed {seed} --video_length {video_length} --smoother_steps 19 20 --is_long_video"
+        command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{resized}' --output_path '{output_path}' --temp_chunk_path 'result' --width {r_width} --height {r_height} --fps {target_fps} --seed {seed} --video_length {video_length} --smoother_steps 19 20 --is_long_video"
     else:
-        command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --temp_chunk_path 'result'  --width 512 --height 512 --fps {target_fps} --seed {seed} --video_length {video_length} --smoother_steps 19 20"
+        command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{resized}' --output_path '{output_path}' --temp_chunk_path 'result'  --width {r_width} --height {r_width} --fps {target_fps} --seed {seed} --video_length {video_length} --smoother_steps 19 20"
     
     try:
         subprocess.run(command, shell=True)
@@ -156,9 +166,9 @@ def run_inference(prompt, video_path, condition, video_length, seed, steps):
     video_path_output = os.path.join(output_path, f"result.mp4")
 
     # Resize to original video input size
-    o_width = get_video_dimension(video_path)[0]
-    o_height = get_video_dimension(video_path)[1]
-    resize_video(video_path_output, 'resized_final.mp4', o_width, o_height, target_fps)
+    #o_width = get_video_dimension(video_path)[0]
+    #o_height = get_video_dimension(video_path)[1]
+    #resize_video(video_path_output, 'resized_final.mp4', o_width, o_height, target_fps)
 
     print(f"FINISHED !")
     return "done", 'resized_final.mp4'