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-rw-r--r--decoder.py251
-rw-r--r--encoder.py105
2 files changed, 164 insertions, 192 deletions
diff --git a/decoder.py b/decoder.py
index 649220c..f9829d5 100644
--- a/decoder.py
+++ b/decoder.py
@@ -1,5 +1,6 @@
import argparse
import collections
+import sys
import cv2
import matplotlib.pyplot as plt
import numpy as np
@@ -7,13 +8,13 @@ from creedsolo import RSCodec
from raptorq import Decoder
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-parser.add_argument("file", help="output file for decoded data")
-parser.add_argument("--len", help="number of bytes to decode", default=2**16, type=int)
-parser.add_argument("--height", help="grid height", default=100, type=int)
-parser.add_argument("--width", help="grid width", default=100, type=int)
-parser.add_argument("--fps", help="framerate", default=30, type=int)
-parser.add_argument("--level", help="error correction level", default=0.1, type=float)
-parser.add_argument("--device", help="camera device index", default=1, type=int)
+parser.add_argument("-i", "--input", help="camera device index or input video file", default=0)
+parser.add_argument("-o", "--output", help="output file for decoded data")
+parser.add_argument("-x", "--height", help="grid height", default=100, type=int)
+parser.add_argument("-y", "--width", help="grid width", default=100, type=int)
+parser.add_argument("-f", "--fps", help="frame rate", default=30, type=int)
+parser.add_argument("-l", "--level", help="error correction level", default=0.1, type=float)
+parser.add_argument("-s", "--size", help="number of bytes to decode", default=2**16, type=int)
args = parser.parse_args()
cheight = cwidth = max(args.height // 10, args.width // 10)
@@ -22,143 +23,127 @@ frame_xor = np.arange(frame_size, dtype=np.uint8)
rs_size = frame_size - int((frame_size + 254) / 255) * int(args.level * 255) - 4
rsc = RSCodec(int(args.level * 255))
-decoder = Decoder.with_defaults(args.len, rs_size)
+decoder = Decoder.with_defaults(args.size, rs_size)
+
+if args.input.isdecimal():
+ args.input = int(args.input)
+cap = cv2.VideoCapture(args.input)
data = None
-# cap = cv2.VideoCapture(args.device)
while data is None:
- # ret, raw_frame = cap.read()
- # if not ret:
- # continue
- # TODO: Try decoding saved videos
- raw_frame = cv2.cvtColor(
- cv2.imread("/home/a/Pictures/Camera/IMG_20240422_000849_027.jpg"),
- cv2.COLOR_BGR2RGB,
- ).astype(np.float64)
-
- X, Y = raw_frame.shape[:2]
- scale = min(X // 20, Y // 20)
- # Resize so smaller dim is 20
- # Use fast default interpolation for factor of 4
- # Then switch to good slow interpolation
- dframe = cv2.resize(
- cv2.resize(raw_frame, (Y // 4, X // 4)),
- (Y // scale, X // scale), # OpenCV swaps them
- interpolation=cv2.INTER_AREA,
- )
- plt.imshow(dframe.astype(np.uint8))
- plt.show()
+ try:
+ ret, raw_frame = cap.read()
+ if not ret:
+ print("End of stream")
+ sys.exit(1)
+ raw_frame = cv2.cvtColor(raw_frame, cv2.COLOR_BGR2RGB).astype(np.float64)
- def max_in_orig(x):
- return tuple(
- np.array(np.unravel_index(np.argmax(x), x.shape)) * scale + scale // 2
+ X, Y = raw_frame.shape[:2]
+ scale = min(X // 20, Y // 20)
+ # Resize so smaller dim is 20
+ # Use fast default interpolation for factor of 4
+ # Then switch to good slow interpolation
+ dframe = cv2.resize(
+ cv2.resize(raw_frame, (Y // 4, X // 4)),
+ (Y // scale, X // scale), # OpenCV swaps them
+ interpolation=cv2.INTER_AREA,
)
+ # plt.imshow(dframe.astype(np.uint8))
+ # plt.show()
- sumframe = np.sum(dframe, axis=2)
- # TODO: Only search in corner area
- widx = max_in_orig((np.std(dframe, axis=2) < 35) * sumframe)
- ridx = max_in_orig(2 * dframe[:, :, 0] - sumframe)
- gidx = max_in_orig(2 * dframe[:, :, 1] - sumframe)
- bidx = max_in_orig(2 * dframe[:, :, 2] - sumframe)
+ def max_in_orig(x):
+ return tuple(np.array(np.unravel_index(np.argmax(x), x.shape)) * scale + scale // 2)
- # Flood fill corners
- def flood_fill(s):
- vis = np.full((X, Y), False)
- vis[s] = True
- queue = collections.deque([s])
- pos = np.array(s)
- col = np.copy(raw_frame[s])
- n = 1
- while len(queue) > 0:
- u = queue.popleft()
- for d in [(5, 0), (0, 5), (-5, 0), (0, -5)]:
- v = (u[0] + d[0], u[1] + d[1])
- if (
- 0 <= v[0] < X
- and 0 <= v[1] < Y
- and not vis[v]
- and np.linalg.norm(raw_frame[v] - raw_frame[s]) < 100
- ):
- vis[v] = True
- pos += np.array(v)
- col += raw_frame[v]
- n += 1
- queue.append(v)
- plt.imshow(raw_frame.astype(np.uint8))
- plt.scatter(*reversed(np.where(vis)))
- plt.scatter(pos[1] / n, pos[0] / n)
- plt.show()
- return pos / n, col / n
+ sumframe = np.sum(dframe, axis=2)
+ # TODO: Only search in corner area
+ widx = max_in_orig((np.std(dframe, axis=2) < 35) * sumframe)
+ ridx = max_in_orig(2 * dframe[:, :, 0] - sumframe)
+ gidx = max_in_orig(2 * dframe[:, :, 1] - sumframe)
+ bidx = max_in_orig(2 * dframe[:, :, 2] - sumframe)
- widx, wcol = flood_fill(widx)
- ridx, rcol = flood_fill(ridx)
- gidx, gcol = flood_fill(gidx)
- bidx, bcol = flood_fill(bidx)
+ # Flood fill corners
+ def flood_fill(s):
+ # TODO: make this faster
+ vis = np.full((X, Y), False)
+ vis[s] = True
+ queue = collections.deque([s])
+ pos = np.array(s)
+ col = np.copy(raw_frame[s])
+ n = 1
+ while len(queue) > 0:
+ u = queue.popleft()
+ for d in [(1, 0), (0, 1), (-1, 0), (0, -1)]:
+ v = (u[0] + d[0], u[1] + d[1])
+ if 0 <= v[0] < X and 0 <= v[1] < Y and not vis[v] and np.linalg.norm(raw_frame[v] - raw_frame[s]) < 125:
+ vis[v] = True
+ pos += np.array(v)
+ col += raw_frame[v]
+ n += 1
+ queue.append(v)
+ # plt.imshow(raw_frame.astype(np.uint8))
+ # plt.scatter(*reversed(np.where(vis)))
+ # plt.scatter(pos[1] / n, pos[0] / n)
+ # plt.show()
+ return pos / n, col / n
- # Find basis of color space
- origin = (rcol + gcol + bcol - wcol) / 2
- rcol -= origin
- gcol -= origin
- bcol -= origin
- print(origin, rcol, gcol, bcol)
- F = 255 * np.linalg.inv(np.stack((rcol, gcol, bcol)).T)
+ widx, wcol = flood_fill(widx)
+ ridx, rcol = flood_fill(ridx)
+ gidx, gcol = flood_fill(gidx)
+ bidx, bcol = flood_fill(bidx)
- # Dumb perspective transform
- xv = np.linspace(
- -(cheight / 2 - 1) / (args.height - cheight + 1),
- 1 + (cheight / 2 - 1) / (args.height - cheight + 1),
- args.height,
- )
- yv = np.linspace(
- -(cwidth / 2 - 1) / (args.width - cwidth + 1),
- 1 + (cwidth / 2 - 1) / (args.width - cwidth + 1),
- args.width,
- )
- xp = (
- np.outer(1 - xv, 1 - yv) * widx[0]
- + np.outer(1 - xv, yv) * ridx[0]
- + np.outer(xv, 1 - yv) * gidx[0]
- + np.outer(xv, yv) * bidx[0]
- )
- yp = (
- np.outer(1 - xv, 1 - yv) * widx[1]
- + np.outer(1 - xv, yv) * ridx[1]
- + np.outer(xv, 1 - yv) * gidx[1]
- + np.outer(xv, yv) * bidx[1]
- )
+ # Find basis of color space
+ origin = (rcol + gcol + bcol - wcol) / 2
+ rcol -= origin
+ gcol -= origin
+ bcol -= origin
+ F = 255 * np.linalg.inv(np.stack((rcol, gcol, bcol)).T)
+
+ # Dumb perspective transform
+ xv = np.linspace(
+ -(cheight / 2 - 1) / (args.height - cheight + 1),
+ 1 + (cheight / 2 - 1) / (args.height - cheight + 1),
+ args.height,
+ )
+ yv = np.linspace(
+ -(cwidth / 2 - 1) / (args.width - cwidth + 1),
+ 1 + (cwidth / 2 - 1) / (args.width - cwidth + 1),
+ args.width,
+ )
+ xp = (
+ np.outer(1 - xv, 1 - yv) * widx[0]
+ + np.outer(1 - xv, yv) * ridx[0]
+ + np.outer(xv, 1 - yv) * gidx[0]
+ + np.outer(xv, yv) * bidx[0]
+ )
+ yp = (
+ np.outer(1 - xv, 1 - yv) * widx[1]
+ + np.outer(1 - xv, yv) * ridx[1]
+ + np.outer(xv, 1 - yv) * gidx[1]
+ + np.outer(xv, yv) * bidx[1]
+ )
- plt.scatter(widx[1], widx[0])
- plt.scatter(ridx[1], ridx[0])
- plt.scatter(gidx[1], gidx[0])
- plt.scatter(bidx[1], bidx[0])
- plt.scatter(yp, xp)
- plt.imshow(raw_frame.astype(np.uint8))
- plt.show()
- print(111111111, xp)
- print(111111111, yp)
+ # plt.scatter(widx[1], widx[0])
+ # plt.scatter(ridx[1], ridx[0])
+ # plt.scatter(gidx[1], gidx[0])
+ # plt.scatter(bidx[1], bidx[0])
+ # plt.scatter(yp, xp)
+ # plt.imshow(raw_frame.astype(np.uint8))
+ # plt.show()
- raw_color_frame = raw_frame[xp.astype(np.int64), yp.astype(np.int64), :]
- print(raw_color_frame)
- color_frame = np.clip(
- np.squeeze(F @ (raw_color_frame - origin)[..., np.newaxis]), 0, 255
- ).astype(np.uint8)
- print(color_frame)
- frame = (
- (color_frame[:, :, 0] >> 5)
- + (color_frame[:, :, 1] >> 3 & 0b00111000)
- + (color_frame[:, :, 2] & 0b11000000)
- )
- frame_data = np.concatenate(
- (
- frame[:cheight, cwidth : args.width - cwidth].flatten(),
- frame[cheight : args.height - cheight].flatten(),
- frame[args.height - cheight :, cwidth : args.width - cwidth].flatten(),
+ raw_color_frame = raw_frame[np.round(xp).astype(np.int64), np.round(yp).astype(np.int64), :]
+ # color_frame = raw_color_frame.astype(np.uint8)
+ color_frame = np.clip(np.squeeze(F @ (raw_color_frame - origin)[..., np.newaxis]), 0, 255).astype(np.uint8)
+ frame = (color_frame[:, :, 0] >> 5) + (color_frame[:, :, 1] >> 2 & 0b00111000) + (color_frame[:, :, 2] & 0b11000000)
+ frame_data = np.concatenate(
+ (
+ frame[:cheight, cwidth : args.width - cwidth].flatten(),
+ frame[cheight : args.height - cheight].flatten(),
+ frame[args.height - cheight :, cwidth : args.width - cwidth].flatten(),
+ )
)
- )
- print(list(frame_data))
- tmp = rsc.decode(frame_data ^ frame_xor)
- # print(tmp, list(tmp[2]), bytes(tmp[0]))
- data = decoder.decode(bytes(tmp))
- break
-with open(args.file, "wb") as f:
+ data = decoder.decode(bytes(rsc.decode(frame_data ^ frame_xor)[0]))
+ print("Decoded frame")
+ except Exception as e:
+ print(e)
+with open(args.output, "wb") as f:
f.write(data)
cap.release()
diff --git a/encoder.py b/encoder.py
index b20cd56..5752d55 100644
--- a/encoder.py
+++ b/encoder.py
@@ -10,27 +10,17 @@ from PIL import Image, ImageQt
from raptorq import Encoder
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-parser.add_argument("file", help="input file")
-parser.add_argument("--height", help="grid height", default=100, type=int)
-parser.add_argument("--width", help="grid width", default=100, type=int)
-parser.add_argument("--fps", help="framerate", default=30, type=int)
-parser.add_argument("--level", help="error correction level", default=0.1, type=float)
-parser.add_argument("--video", help="output file for encoded video")
-parser.add_argument("--scale", help="scale of new frames", default=2, type=int)
+parser.add_argument("-i", "--input", help="input file")
+parser.add_argument("-o", "--output", help="output video file")
+parser.add_argument("-x", "--height", help="grid height", default=100, type=int)
+parser.add_argument("-y", "--width", help="grid width", default=100, type=int)
+parser.add_argument("-f", "--fps", help="frame rate", default=30, type=int)
+parser.add_argument("-l", "--level", help="error correction level", default=0.1, type=float)
+parser.add_argument("-m", "--mix", help="mix frames with original video", action="store_true")
args = parser.parse_args()
-if args.video:
- cap = cv2.VideoCapture(args.file)
- args.height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT) / args.scale)
- args.width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH) / args.scale)
-
-# Make corners
cheight = cwidth = max(args.height // 10, args.width // 10)
-wcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b11111111), ((0, 1), (0, 1)))
-rcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b00000111), ((0, 1), (1, 0)))
-gcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b00111000), ((1, 0), (0, 1)))
-bcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b11000000), ((1, 0), (1, 0)))
midwidth = args.width - 2 * cwidth
frame_size = args.height * args.width - 4 * cheight * cwidth
frame_xor = np.arange(frame_size, dtype=np.uint8)
@@ -38,12 +28,18 @@ frame_xor = np.arange(frame_size, dtype=np.uint8)
# raptorq can add up to 4 extra bytes
rs_size = frame_size - int((frame_size + 254) / 255) * int(args.level * 255) - 4
-with open(args.file, "rb") as f:
+with open(args.input, "rb") as f:
data = f.read()
rsc = RSCodec(int(args.level * 255))
encoder = Encoder.with_defaults(data, rs_size)
packets = encoder.get_encoded_packets(int(len(data) / rs_size * args.level))
+# Make corners
+wcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b11111111), ((0, 1), (0, 1)))
+rcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b00000111), ((0, 1), (1, 0)))
+gcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b00111000), ((1, 0), (0, 1)))
+bcorner = np.pad(np.full((cheight - 1, cwidth - 1), 0b11000000), ((1, 0), (1, 0)))
+
print("Data length:", len(data))
print("Packets:", len(packets))
@@ -55,38 +51,26 @@ def get_frame():
frame_data = np.array(rsc.encode(packets[idx]))
# Pad frame to fit frame_size since raptorq might not add 4 bytes
frame_data = np.pad(frame_data, (0, frame_size - len(frame_data))) ^ frame_xor
+ if idx == 0:
+ print(list(frame_data))
idx = (idx + 1) % len(packets)
frame = np.concatenate(
(
np.concatenate(
- (
- wcorner,
- frame_data[: cheight * midwidth].reshape((cheight, midwidth)),
- rcorner,
- ),
+ (wcorner, frame_data[: cheight * midwidth].reshape((cheight, midwidth)), rcorner),
axis=1,
),
frame_data[cheight * midwidth : frame_size - cheight * midwidth].reshape(
(args.height - 2 * cheight, args.width)
),
np.concatenate(
- (
- gcorner,
- frame_data[frame_size - cheight * midwidth :].reshape(
- (cheight, midwidth)
- ),
- bcorner,
- ),
+ (gcorner, frame_data[frame_size - cheight * midwidth :].reshape((cheight, midwidth)), bcorner),
axis=1,
),
)
)
return np.stack(
- (
- (frame & 0b00000111) * 255 // 7,
- (frame >> 3 & 0b00000111) * 255 // 7,
- (frame >> 6 & 0b00000011) * 255 // 3,
- ),
+ ((frame & 0b00000111) * 255 // 7, (frame >> 3 & 0b00000111) * 255 // 7, (frame >> 6) * 255 // 3),
axis=-1,
).astype(np.uint8)
@@ -111,30 +95,33 @@ class EncoderWidget(QWidget):
self.label.setPixmap(pixmap)
-if args.video:
- out = cv2.VideoWriter(
- args.video,
- cv2.VideoWriter_fourcc(*"mp4v"),
- cap.get(cv2.CAP_PROP_FPS),
- (args.scale * args.width, args.scale * args.height),
- )
- while cap.isOpened():
- ret, frame = cap.read()
- if not ret:
- break
- frame[: args.scale * cheight, : args.scale * cwidth] = 255
- frame[: args.scale * cheight, args.scale * (args.width - cwidth) :] = 255
- frame[args.scale * (args.height - cheight) :, : args.scale * cwidth] = 255
- frame[
- args.scale * (args.height - cheight) :, args.scale * (args.width - cwidth) :
- ] = 255
- out.write(
- (
- frame.astype(np.int64)
- * np.repeat(np.repeat(get_frame(), args.scale, 0), args.scale, 1)
- / 255
- ).astype(np.uint8)
- )
+if args.output:
+ if args.mix:
+ cap = cv2.VideoCapture(args.input)
+ height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+ width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+ hscale = height // args.height
+ wscale = width // args.width
+ out = cv2.VideoWriter(args.output, cv2.VideoWriter_fourcc(*"mp4v"), args.fps, (width, height))
+ while cap.isOpened():
+ ret, frame = cap.read()
+ if not ret:
+ break
+ frame = frame.astype(np.float64) / 255
+ frame[: hscale * cheight, : wscale * cwidth] = 1
+ frame[: hscale * cheight, wscale * (args.width - cwidth) :] = 1
+ frame[hscale * (args.height - cheight) :, : wscale * cwidth] = 1
+ frame[hscale * (args.height - cheight) :, wscale * (args.width - cwidth) :] = 1
+ out.write(
+ cv2.cvtColor(
+ (frame * np.repeat(np.repeat(get_frame(), hscale, 0), wscale, 1)).astype(np.uint8),
+ cv2.COLOR_RGB2BGR,
+ )
+ )
+ else:
+ out = cv2.VideoWriter(args.output, cv2.VideoWriter_fourcc(*"mp4v"), args.fps, (4* args.width, 4*args.height))
+ for _ in packets:
+ out.write(cv2.cvtColor(np.repeat(np.repeat(get_frame(), 4, 0), 4, 1), cv2.COLOR_RGB2BGR))
else:
input("Seizure warning!")
app = QApplication([])