mirror of
https://github.com/KrisKennaway/ii-vision.git
synced 2025-01-20 14:31:35 +00:00
Read video frame rate and encode a new frame when the cycle count
has ticked past the appropriate time. - optimize the frame encoding a bit - use int64 consistently to avoid casting Fix a bug - when retiring an offset, also update our memory map with the new content, oops If we run out of changes to index, keep emitting stores for content at page=32,offset=0 forever Switch to a weighted D-L implementation so we can weight e.g. different substitutions differently (e.g. weighting diffs to/from black pixels differently than color errors)
This commit is contained in:
kris
parent
aed439c0b3
commit
7db5c1c444
1
audio.py
1
audio.py
@ -25,7 +25,6 @@ class Audio:
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def audio_stream(self):
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with audioread.audio_open(self.filename) as f:
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for buf in f.read_data(128 * 1024):
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print(f.channels, f.samplerate, f.duration)
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data = np.frombuffer(buf, dtype='int16').astype(
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'float32').reshape((f.channels, -1), order='F')
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16
main.py
16
main.py
@ -1,18 +1,20 @@
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import frame_grabber
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import movie
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import opcodes
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import screen
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import video
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MAX_OUT = 10 * 1024 * 1024
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MAX_OUT = 100 * 1024 * 1024
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VIDEO_FPS = 30
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APPLE_FPS = 30
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def main():
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filename = "Computer Chronicles - 06x05 - The Apple II.mp4"
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filename = "apple_ii_forever.m4v"
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m = movie.Movie(filename, audio_normalization=3.0)
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# filename = "Computer Chronicles - 06x05 - The Apple II.mp4"
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# filename = (
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# "Rick Astley - Never Gonna Give You Up (Official "
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# "Music Video).mp4"
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# )
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m = movie.Movie(filename, audio_normalization=2.0)
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with open("out.bin", "wb") as out:
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for bytes_out, b in enumerate(m.emit_stream(m.encode())):
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28
movie.py
28
movie.py
@ -3,22 +3,18 @@
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from typing import Iterable, Iterator
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import audio
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import frame_grabber
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import opcodes
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import video
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class Movie:
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def __init__(self, filename: str, audio_normalization:float=1.0):
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def __init__(self, filename: str, audio_normalization: float = 1.0):
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self.filename = filename # type: str
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self.audio = audio.Audio(
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filename, normalization=audio_normalization) # type: audio.Audio
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# TODO: get from input file
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self.video = video.Video() # type: video.Video
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self.video = video.Video(filename) # type: video.Video
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self.cycles = 0
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self.ticks_per_video_frame = (
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self.audio.sample_rate / self.video.frame_rate)
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self.stream_pos = 0 # type: int
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@ -32,26 +28,16 @@ class Movie:
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self._last_op = opcodes.Nop()
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def frames(self):
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yield from frame_grabber.bmp2dhr_frame_grabber(self.filename)
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def encode(self) -> Iterator[opcodes.Opcode]:
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ticks = 0
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frames = 0
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video_frames = self.video.frames()
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video_seq = None
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video_frames = self.frames()
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for au in self.audio.audio_stream():
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if ticks % self.ticks_per_video_frame == 0:
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frames += 1
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video_seq = self.video.encode_frame(next(video_frames))
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print("Starting frame %d" % frames)
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# TODO: compute similarity
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ticks += 1
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self.cycles += self.audio.cycles_per_tick
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if self.video.tick(self.cycles):
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print("Starting frame %d" % self.video.frame_number)
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video_frame = next(video_frames)
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video_seq = self.video.encode_frame(video_frame)
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# au has range -15 .. 16 (step=1)
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# Tick cycles are units of 2
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290
video.py
290
video.py
@ -1,13 +1,19 @@
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import functools
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import heapq
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import random
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from typing import Iterator, Tuple, Iterable
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import os
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import threading
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import queue
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import subprocess
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from typing import List, Iterator, Tuple, Iterable
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from PIL import Image
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import numpy as np
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from similarity.damerau import Damerau
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import skvideo.io
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import weighted_levenshtein
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import opcodes
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import scheduler
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import screen
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@ -19,14 +25,40 @@ def hamming_weight(n):
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return n
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@functools.lru_cache(None)
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def edit_weight(a: int, b: int, is_odd_offset: bool):
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d = Damerau()
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# K G V W
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# O B
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error_substitute_costs = np.ones((128, 128), dtype=np.float64)
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# Penalty for turning on/off a black bit
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for c in "01GVWOB":
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error_substitute_costs[(ord('K'), ord(c))] = 5
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error_substitute_costs[(ord(c), ord('K'))] = 5
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# Penalty for changing colour
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for c in "01GVWOB":
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for d in "01GVWOB":
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error_substitute_costs[(ord(c), ord(d))] = 1
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error_substitute_costs[(ord(d), ord(c))] = 1
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insert_costs = np.ones(128, dtype=np.float64) * 1000
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delete_costs = np.ones(128, dtype=np.float64) * 1000
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@functools.lru_cache(None)
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def edit_weight(a: int, b: int, is_odd_offset: bool, error=False):
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a_pixels = byte_to_colour_string(a, is_odd_offset)
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b_pixels = byte_to_colour_string(b, is_odd_offset)
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return d.distance(a_pixels, b_pixels)
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substitute_costs = error_substitute_costs # if error else None
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dist = weighted_levenshtein.dam_lev(
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a_pixels, b_pixels,
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insert_costs=insert_costs,
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delete_costs=delete_costs,
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substitute_costs=substitute_costs,
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)
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return np.int64(dist)
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@functools.lru_cache(None)
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@ -76,42 +108,101 @@ class Video:
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def __init__(
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self,
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frame_rate: int = 30,
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screen_page: int = 1,
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opcode_scheduler: scheduler.OpcodeScheduler = None):
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self.screen_page = screen_page
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self.frame_rate = frame_rate
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filename: str):
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self.filename = filename # type: str
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self._reader = skvideo.io.FFmpegReader(filename)
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# Compute frame rate from input video
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data = skvideo.io.ffprobe(self.filename)['video']
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rate_data = data['@r_frame_rate'].split("/") # e.g. 12000/1001
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self._input_frame_rate = float(rate_data[0]) / float(rate_data[1])
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self.cycles_per_frame = 1024. * 1024 / self._input_frame_rate
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self.frame_number = 0
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# Initialize empty
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self.memory_map = screen.MemoryMap(
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self.screen_page) # type: screen.MemoryMap
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self.scheduler = (
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opcode_scheduler or scheduler.HeuristicPageFirstScheduler())
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screen_page=1) # type: screen.MemoryMap
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# Accumulates pending edit weights across frames
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self.update_priority = np.zeros((32, 256), dtype=np.int)
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self.update_priority = np.zeros((32, 256), dtype=np.int64)
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def tick(self, cycles) -> bool:
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# print(cycles, self.cycles_per_frame, self.cycles_per_frame *
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# self.frame_number)
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if cycles > (self.cycles_per_frame * self.frame_number):
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self.frame_number += 1
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return True
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return False
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def encode_frame(self, target: screen.MemoryMap) -> Iterator[
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opcodes.Opcode]:
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"""Update to match content of frame within provided budget.
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def _frame_grabber(self):
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for frame_array in self._reader.nextFrame():
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yield Image.fromarray(frame_array)
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def frames(self) -> Iterator[screen.MemoryMap]:
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"""Encode frame to HGR using bmp2dhr.
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We do the encoding in a background thread to parallelize.
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"""
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frame_dir = self.filename.split(".")[0]
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try:
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os.mkdir(frame_dir)
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except FileExistsError:
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pass
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q = queue.Queue(maxsize=10)
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def worker():
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for _idx, _frame in enumerate(self._frame_grabber()):
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outfile = "%s/%08dC.BIN" % (frame_dir, _idx)
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bmpfile = "%s/%08d.bmp" % (frame_dir, _idx)
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try:
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os.stat(outfile)
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except FileNotFoundError:
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_frame = _frame.resize((280, 192))
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_frame.save(bmpfile)
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subprocess.call(
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["/usr/local/bin/bmp2dhr", bmpfile, "hgr", "D9"])
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os.remove(bmpfile)
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_frame = np.fromfile(outfile, dtype=np.uint8)
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q.put(_frame)
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q.put(None)
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t = threading.Thread(target=worker)
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t.start()
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while True:
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frame = q.get()
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if frame is None:
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break
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yield screen.FlatMemoryMap(
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screen_page=1, data=frame).to_memory_map()
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q.task_done()
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t.join()
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def encode_frame(
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self, target: screen.MemoryMap
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) -> Iterator[opcodes.Opcode]:
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"""Update to match content of frame within provided budget."""
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print("Similarity %f" % (self.update_priority.mean()))
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yield from self._index_changes(self.memory_map, target)
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def _index_changes(
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def _diff_weights(
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self,
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source: screen.MemoryMap,
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target: screen.MemoryMap
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) -> Iterator[Tuple[int, int, int, int, int]]:
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"""Transform encoded screen to sequence of change tuples.
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Change tuple is (update_priority, page, offset, content, run_length)
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"""
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diff_weights = np.zeros((32, 256), dtype=np.uint8)
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):
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diff_weights = np.zeros((32, 256), dtype=np.int64)
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it = np.nditer(
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source.page_offset ^ target.page_offset, flags=['multi_index'])
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@ -127,16 +218,9 @@ class Video:
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it.multi_index[1] % 2 == 1
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)
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it.iternext()
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return diff_weights
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# Clear any update priority entries that have resolved themselves
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# with new frame
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self.update_priority[diff_weights == 0] = 0
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self.update_priority += diff_weights
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# Iterate in descending order of update priority and emit tuples
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# encoding (page, content, [offsets])
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def _heapify_priorities(self) -> List:
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priorities = []
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it = np.nditer(self.update_priority, flags=['multi_index'])
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while not it.finished:
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@ -147,69 +231,107 @@ class Video:
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page, offset = it.multi_index
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# Don't use deterministic order for page, offset
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nonce = random.randint(0,255)
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nonce = random.random()
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heapq.heappush(priorities, (-priority, nonce, page, offset))
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it.iternext()
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while True:
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priority, _, page, offset = heapq.heappop(priorities)
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priority = -priority
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if page > (56-32):
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return priorities
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@functools.lru_cache(None)
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def _compute_delta(self, content, target, old, is_odd):
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return edit_weight(content, target, is_odd, error=True) - old
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def _compute_error(self, page, content, target, old_error):
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offsets = []
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old_error_page = old_error[page]
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tpo = target.page_offset[page]
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page_priorities = [(-p, random.random(), o) for o, p in enumerate(
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self.update_priority[page]) if p]
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heapq.heapify(page_priorities)
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# Iterate in descending priority order and take first 3 offsets with
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# negative delta
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while page_priorities:
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_, _, o = heapq.heappop(page_priorities)
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# If we store content at this offset, what is the difference
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# between this edit distance and the ideal target edit distance?
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delta = self._compute_delta(
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content, tpo[o], o % 2 == 1, old_error_page[o])
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# Getting further away from goal, no thanks!
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if delta >= 0:
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continue
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#
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# # print("Offset %d prio %d: %d -> %d = %d" % (
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# # o, p, content,
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# # target.page_offset[page, o],
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# # delta
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# # ))
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offsets.append(o)
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if len(offsets) == 3:
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break
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return offsets
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def _index_changes(
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self,
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source: screen.MemoryMap,
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target: screen.MemoryMap
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) -> Iterator[Tuple[int, int, int, int, int]]:
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"""Transform encoded screen to sequence of change tuples.
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Change tuple is (update_priority, page, offset, content, run_length)
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"""
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diff_weights = self._diff_weights(source, target)
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# Clear any update priority entries that have resolved themselves
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# with new frame
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self.update_priority[diff_weights == 0] = 0
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self.update_priority += diff_weights
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priorities = self._heapify_priorities()
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while priorities:
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_, _, page, offset = heapq.heappop(priorities)
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# Check whether we've already cleared this diff while processing
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# an earlier opcode
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if self.update_priority[page, offset] == 0:
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continue
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offsets = [offset]
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content = target.page_offset[page, offset]
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#print("Priority %d: page %d offset %d content %d" % (
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# print("Priority %d: page %d offset %d content %d" % (
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# priority, page, offset, content))
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# Clear priority for the offset we're emitting
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self.update_priority[page, offset] = 0
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self.memory_map.page_offset[page, offset] = content
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# Need to find 3 more offsets to fill this opcode
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# Minimize the update_priority delta that would result from
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# emitting this offset
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# Find offsets that would have largest reduction in diff weight
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# with this content byte, then order by update priority
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deltas = {}
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for o, p in enumerate(self.update_priority[page]):
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if p == 0:
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continue
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# If we store content at this offset, what is the new
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# edit_weight from this content byte to the target
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delta = edit_weight(
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for o in self._compute_error(
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page,
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content,
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target.page_offset[page, o],
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o % 2 == 1
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)
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#print("Offset %d prio %d: %d -> %d = %d" % (
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# o, p, content,
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# target.page_offset[page, o],
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# delta
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#))
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deltas.setdefault(delta, list()).append((p, o))
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target,
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diff_weights
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):
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offsets.append(o)
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# Clear priority for the offset we're emitting
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self.update_priority[page, o] = 0
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self.memory_map.page_offset[page, o] = content
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for d in sorted(deltas.keys()):
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#print(d)
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po = sorted(deltas[d], reverse=True)
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#print(po)
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for p, o in po:
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offsets.append(o)
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# Clear priority for the offset we're emitting
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self.update_priority[page, offset] = 0
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if len(offsets) == 4:
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break
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if len(offsets) == 4:
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break
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# Pad to 4 if we didn't find anything
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# Pad to 4 if we didn't find enough
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for _ in range(len(offsets), 4):
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offsets.append(offsets[0])
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#print("Page %d, content %d: offsets %s" % (page+32, content,
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# print("Page %d, content %d: offsets %s" % (page+32, content,
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# offsets))
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yield (page+32, content, offsets)
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yield (page + 32, content, offsets)
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# If we run out of things to do, pad forever
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content = target.page_offset[(0, 0)]
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while True:
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yield (32, content, [0, 0, 0, 0])
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