autism_plus_edynamix_demo_15

src/minicpm/response.py

@@ -3,7 +3,7 @@ import sys
 import gradio as gr
 import spaces
 from decord import VideoReader, cpu
-from PIL import Image
+# from PIL import Image
 # Local imports
 from src.config import (
     device,
@@ -21,22 +21,22 @@ from src.exception import CustomExceptionHandling
 model, tokenizer, processor = load_model_tokenizer_and_processor(model_name, device)
 MAX_NUM_FRAMES=64
 
-def encode_video(video_path):
-    MAX_NUM_FRAMES=64
-    def uniform_sample(l, n):
-        gap = len(l) / n
-        idxs = [int(i * gap + gap / 2) for i in range(n)]
-        return [l[i] for i in idxs]
+# def encode_video(video_path):
+#     MAX_NUM_FRAMES=64
+#     def uniform_sample(l, n):
+#         gap = len(l) / n
+#         idxs = [int(i * gap + gap / 2) for i in range(n)]
+#         return [l[i] for i in idxs]
 
-    vr = VideoReader(video_path, ctx=cpu(0))
-    sample_fps = round(vr.get_avg_fps() / 1)  # FPS
-    frame_idx = [i for i in range(0, len(vr), sample_fps)]
-    if len(frame_idx) > MAX_NUM_FRAMES:
-        frame_idx = uniform_sample(frame_idx, MAX_NUM_FRAMES)
-    frames = vr.get_batch(frame_idx).asnumpy()
-    frames = [Image.fromarray(v.astype('uint8')) for v in frames]
-    print('num frames:', len(frames))
-    return frames
+#     vr = VideoReader(video_path, ctx=cpu(0))
+#     sample_fps = round(vr.get_avg_fps() / 1)  # FPS
+#     frame_idx = [i for i in range(0, len(vr), sample_fps)]
+#     if len(frame_idx) > MAX_NUM_FRAMES:
+#         frame_idx = uniform_sample(frame_idx, MAX_NUM_FRAMES)
+#     frames = vr.get_batch(frame_idx).asnumpy()
+#     frames = [Image.fromarray(v.astype('uint8')) for v in frames]
+#     print('num frames:', len(frames))
+#     return frames
 
 @spaces.GPU(duration=120)
 def describe_image(