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* nv: minimal hevc * validate * not needed * tralin * var * cpu * fxi * desc * move * cleanup
72 lines
3.0 KiB
Python
72 lines
3.0 KiB
Python
import argparse, os, hashlib
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from tinygrad.helpers import getenv, DEBUG, round_up, Timing, tqdm, fetch
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from extra.hevc.hevc import parse_hevc_file_headers, untile_nv12, to_bgr, nv_gpu
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from tinygrad import Tensor, dtypes, Device, Variable
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--input_file", type=str, default="")
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parser.add_argument("--output_dir", type=str, default="extra/hevc/out")
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args = parser.parse_args()
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os.makedirs(args.output_dir, exist_ok=True)
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if args.input_file == "":
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url = "https://github.com/haraschax/filedump/raw/09a497959f7fa6fd8dba501a25f2cdb3a41ecb12/comma_video.hevc"
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hevc_tensor = Tensor.from_url(url, device="CPU")
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else:
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hevc_tensor = Tensor.empty(os.stat(args.input_file).st_size, dtype=dtypes.uint8, device=f"disk:{args.input_file}").to("CPU")
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dat = bytes(hevc_tensor.data())
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dat_hash = hashlib.md5(dat).hexdigest()
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with Timing("prep infos: "):
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dat_nv = hevc_tensor.to("NV")
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opaque, frame_info, w, h, luma_w, luma_h, chroma_off = parse_hevc_file_headers(dat)
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frame_info = frame_info[:getenv("MAX_FRAMES", len(frame_info))]
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# move all needed data to gpu
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all_slices = []
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with Timing("prep slices to gpu: "):
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opaque_nv = opaque.to("NV").contiguous().realize()
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for i, (offset, sz, frame_pos, history_sz, _) in enumerate(frame_info):
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all_slices.append(hevc_tensor[offset:offset+sz].to("NV").contiguous().realize())
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Device.default.synchronize()
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out_image_size = luma_h + (luma_h + 1) // 2, round_up(luma_w, 64)
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max_hist = max(history_sz for _, _, _, history_sz, _ in frame_info)
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pos = Variable("pos", 0, max_hist + 1)
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history = []
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out_images = []
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with Timing("decoding whole file: ", on_exit=(lambda et: f", {len(frame_info)} frames, {len(frame_info)/(et/1e9):.2f} fps")):
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for i, (offset, sz, frame_pos, history_sz, is_hist) in enumerate(frame_info):
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history = history[-history_sz:] if history_sz > 0 else []
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outimg = all_slices[i].decode_hevc_frame(pos.bind(frame_pos), out_image_size, opaque_nv[i], history).realize()
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out_images.append(outimg)
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if is_hist: history.append(outimg)
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Device.default.synchronize()
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if getenv("VALIDATE", 0):
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import pickle
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if dat_hash == "b813bfdbec194fd17fdf0e3ceb8cea1c":
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url = "https://github.com/nimlgen/hevc_validate_set/raw/refs/heads/main/decoded_frames_b813bfdbec194fd17fdf0e3ceb8cea1c.pkl"
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decoded_frames = pickle.load(fetch(url).open("rb"))
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else: decoded_frames = pickle.load(open(f"extra/hevc/decoded_frames_{dat_hash}.pkl", "rb"))
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else: import cv2
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for i, img in tqdm(enumerate(out_images)):
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if getenv("VALIDATE", 0):
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if i < len(decoded_frames) and len(decoded_frames[i]) > 0:
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img = untile_nv12(img, h, w, luma_w, chroma_off).realize()
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assert img.data() == decoded_frames[i], f"Frame {i} does not match reference decoder!"
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print(f"Frame {i} matches reference decoder!")
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else:
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img = to_bgr(img, h, w, luma_w, chroma_off).realize()
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cv2.imwrite(f"{args.output_dir}/out_frame_{i:04d}.png", img.numpy())
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