diff --git a/inference_mp4.py b/inference_mp4.py
new file mode 100644
index 0000000..17a790a
--- /dev/null
+++ b/inference_mp4.py
@@ -0,0 +1,115 @@
+import os
+import cv2
+import torch
+import argparse
+import numpy as np
+from tqdm import tqdm
+from torch.nn import functional as F
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+if torch.cuda.is_available():
+    torch.set_grad_enabled(False)
+    torch.backends.cudnn.enabled = True
+    torch.backends.cudnn.benchmark = True
+
+parser = argparse.ArgumentParser(description='Interpolation for a pair of images')
+parser.add_argument('--video', dest='video', required=True)
+parser.add_argument('--montage', dest='montage', action='store_true', help='montage origin video')
+parser.add_argument('--skip', dest='skip', action='store_true', help='whether to remove static frames before processing')
+parser.add_argument('--fps', dest='fps', type=int, default=None)
+parser.add_argument('--png', dest='png', action='store_true', help='whether to output png format outputs')
+parser.add_argument('--ext', dest='ext', type=str, default='mp4', help='output video extension')
+parser.add_argument('--times', dest='times', type=int, default=1)
+args = parser.parse_args()
+
+from model.RIFE import Model
+model = Model()
+model.load_model('./train_log')
+model.eval()
+model.device()
+
+videoCapture = cv2.VideoCapture(args.video)
+fps = np.round(videoCapture.get(cv2.CAP_PROP_FPS))
+if args.fps is None:
+    fps = args.fps * 2
+success, frame = videoCapture.read()
+h, w, _ = frame.shape
+fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
+if args.png:
+    if not os.path.exists('output'):
+        os.mkdir('output')
+else:
+    video_path_wo_ext, ext = os.path.splitext(args.video)
+    output = cv2.VideoWriter('{}_{}fps.{}'.format(video_path_wo_ext, args.fps, args.ext), fourcc, args.fps, (w, h))
+    
+cnt = 0
+def writeframe(frame):
+    global cnt
+    if args.png:
+        cv2.imwrite('output/{:0>7d}.png'.format(cnt), frame)
+        cnt += 1
+    else:
+        output.write(frame)
+if args.montage:
+    left = w // 4
+    w = w // 2
+ph = ((h - 1) // 32 + 1) * 32
+pw = ((w - 1) // 32 + 1) * 32
+padding = (0, pw - w, 0, ph - h)
+tot_frame = videoCapture.get(cv2.CAP_PROP_FRAME_COUNT)
+print('{}.{}, {} frames in total, {}FPS to {}FPS'.format(video_path_wo_ext, args.ext, tot_frame, fps, args.fps))
+pbar = tqdm(total=tot_frame)
+skip_frame = 1
+if args.montage:
+    frame = frame[:, left: left + w]
+while success:
+    lastframe = frame
+    success, frame = videoCapture.read()
+    if success:
+        if args.montage:
+            frame = frame[:, left: left + w]
+        I0 = torch.from_numpy(np.transpose(lastframe, (2,0,1)).astype("float32") / 255.).to(device).unsqueeze(0)
+        I1 = torch.from_numpy(np.transpose(frame, (2,0,1)).astype("float32") / 255.).to(device).unsqueeze(0)
+        I0 = F.pad(I0, padding)
+        I1 = F.pad(I1, padding)
+        p = (F.interpolate(I0, (16, 16), mode='bilinear', align_corners=False)
+             - F.interpolate(I1, (16, 16), mode='bilinear', align_corners=False)).abs().mean()
+        if p < 1e-3 and args.skip:
+            if skip_frame % 100 == 0:
+                print("Warning: Your video has {} static frames, skipping them may change the duration of the generated video.".format(skip_frame))
+            skip_frame += 1
+            pbar.update(1)
+            continue
+        if p > 0.2:             
+            mid1 = lastframe
+            mid0 = lastframe
+            mid2 = frame
+        else:
+            mid1 = model.inference(I0, I1)
+            if args.times == 2:
+                mid = model.inference(torch.cat((I0, mid1), 0), torch.cat((mid1, I1), 0))
+            mid1 = (((mid1[0] * 255.).cpu().detach().numpy().transpose(1, 2, 0))).astype('uint8')
+            if args.times == 2:
+                mid0 = (((mid[0] * 255.).cpu().detach().numpy().transpose(1, 2, 0))).astype('uint8')
+                mid2 = (((mid[1]* 255.).cpu().detach().numpy().transpose(1, 2, 0))).astype('uint8')
+        if args.montage:
+            writeframe(np.concatenate((lastframe, lastframe), 1))
+            if args.times == 2:
+                writeframe(np.concatenate((lastframe, mid0[:h, :w]), 1))
+            writeframe(np.concatenate((lastframe, mid1[:h, :w]), 1))
+            if args.times == 2:
+                writeframe(np.concatenate((lastframe, mid2[:h, :w]), 1))
+        else:
+            writeframe(lastframe)
+            if args.times == 2:
+                writeframe(mid0[:h, :w])
+            writeframe(mid1[:h, :w])
+            if args.times == 2:
+                writeframe(mid2[:h, :w])
+        pbar.update(1)
+if args.montage:
+    writeframe(np.concatenate((lastframe, lastframe), 1))
+else:
+    writeframe(lastframe)
+pbar.close()
+output.release()