Spaces:
Sleeping
Sleeping
File size: 2,169 Bytes
92076a7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | import time
import numpy as np
import torch
from PIL import Image
def tensor_to_image(frame: torch.Tensor) -> Image.Image:
"""Convert [3, H, W] or [1, 3, H, W] float tensor to PIL Image."""
f = frame.detach().cpu().float()
if f.dim() == 4:
f = f.squeeze(0)
arr = f.permute(1, 2, 0).numpy()
arr = ((arr - arr.min()) / (arr.max() - arr.min() + 1e-8) * 255).astype(np.uint8)
return Image.fromarray(arr)
class TkPlayer:
"""Simple tkinter video player.
Decodes chunks through the pipeline and displays frames in a
window at the source frame rate. Close the window to stop.
"""
def __init__(self, pipeline, layer_mask: int = 0b111111):
self.pipeline = pipeline
self.layer_mask = layer_mask
def play(self):
reader = self.pipeline.reader
fps = reader.header.fps or 30
frame_time = 1.0 / fps
frames = []
for chunk in self.pipeline.decode_all(layer_mask=self.layer_mask):
for t in range(chunk.shape[2]):
frames.append(chunk[:, :, t])
if not frames:
raise RuntimeError("no frames decoded")
import tkinter as tk
from PIL import ImageTk
root = tk.Tk()
root.title(f"MediaTok — {reader.path}")
label = tk.Label(root)
label.pack()
first = tensor_to_image(frames[0])
photo = ImageTk.PhotoImage(first)
label.configure(image=photo)
root.geometry(f"{first.width}x{first.height}")
state = {"index": 1, "photo": photo, "last": time.perf_counter()}
def advance():
if state["index"] >= len(frames):
root.destroy()
return
img = tensor_to_image(frames[state["index"]])
state["photo"] = ImageTk.PhotoImage(img)
label.configure(image=state["photo"])
state["index"] += 1
elapsed = time.perf_counter() - state["last"]
state["last"] = time.perf_counter()
delay = max(1, int((frame_time - elapsed) * 1000))
root.after(delay, advance)
root.after(0, advance)
root.mainloop()
|