feat(test): add sync prepare

pyproject.toml

@@ -33,3 +33,8 @@ package-data = { "flandre.assets" = ["*.svg", "*.png"], "flandre.pyqt" = ["*.ui"
 
 [project.scripts]
 flandre = "flandre.launcher:entrypoint"
+
+[project.optional-dependencies]
+to = [
+    "nvidia-nvimgcodec-cu12>=0.5.0.13",
+]

test/sync_time.py

@@ -1,23 +1,41 @@
+import matplotlib.pyplot as plt
 import json
 from pathlib import Path
 import itertools
 
+import numpy as np
+
 from flandre.utils.RfFrame import b2t
 
 
 rec_folder = Path(
-    '/run/media/lambda/b86dccdc-f134-464b-a310-6575ee9ae85c/record/')
+    '/run/media/lambda/b86dccdc-f134-464b-a310-6575ee9ae85c/record2/')
 
 robot_folder = rec_folder / 'robot'
 device_folder = rec_folder / 'device'
 camera_folder = rec_folder / 'camera'
 
-device_ts_map = {int(file.stem): file for file in device_folder.glob('*')}
+device_ts_map = {int(file.stem): file for file in device_folder.glob('*.bin')}
-camera_ts_map = {int(file.stem): file for file in camera_folder.glob('*')}
+camera_ts_map = {int(file.stem): file for file in camera_folder.glob('*.jpg')}
 
-js = itertools.chain(*[json.loads(file.read_text())
+robot_ts_map = {int(k): v for k, v in json.loads(
-                     for file in robot_folder.glob('*')])
+    (rec_folder/'robot.json').read_text()).items()}
-robot_ts_map = {v['host_ts']: v for v in js}
+
+device_host_arr = np.array(sorted(device_ts_map.keys()))
+
+device_device_list: list[int] = []
+for k in device_host_arr:
+    seq, encoder, host_ts, device_deivce, buffer = b2t(
+        device_ts_map[k].open('rb').read(100))
+    device_device_list.append(device_deivce)
+
+device_device_arr = np.array(device_device_list)
+
+robot_host_arr = sorted(robot_ts_map.keys())
+
+
+robot_device_arr = np.array([robot_ts_map[k]['device_ts']
+                            for k in robot_host_arr])
 
 
 def func(a: int, b: list[int]):
@@ -32,36 +50,72 @@ def func(a: int, b: list[int]):
       The largest number in `b` <= `a`, or None if no such number exists.
     """
     # Create a new list containing only the numbers from b that are <= a
-    candidates = [num for num in b if num <= a]
 
-    # If the candidates list is not empty, return the largest number from it
+    arr = np.array(b)
-    if candidates:
+    arr -= a
-        return max(candidates)
+    arr = np.abs(arr)
-    else:
+    argmin = np.argmin(arr)
-        # If no number in b was less than or equal to a, return None
+    m = b[argmin]
-        return None
+    return m, a-m
 
 
 # print(device_ts_map.__len__())
 # print(robot_ts_map.__len__())
 
-ass = sorted(list(device_ts_map.keys()))[50:-100]
+ass = sorted(list(device_ts_map.keys()))[500:-1500]
-a0 = ass[0]
+device_host0 = ass[0]
-a1 = ass[-1]
+device_host1 = ass[-1]
 
-print((a1-a0)*10**-9)
 
-r0 = robot_ts_map[func(a0, list(robot_ts_map.keys()))]['device_ts']
+m0, robot_d0 = func(device_host0, sorted(list(robot_ts_map.keys())))
-r1 = robot_ts_map[func(a1, list(robot_ts_map.keys()))]['device_ts']
+robot_device0 = robot_ts_map[m0]['device_ts']
+m1, robot_d1 = func(device_host1, sorted(list(robot_ts_map.keys())))
+robot_device1 = robot_ts_map[m1]['device_ts']
 
-seq, encoder, host_ts, device_ts0, buffer = b2t(device_ts_map[a0].read_bytes())
+camera_host0, camera_d0 = func(
-print(device_ts0)
+    device_host0, sorted(list(camera_ts_map.keys())))
-seq, encoder, host_ts, device_ts1, buffer = b2t(device_ts_map[a1].read_bytes())
+camera_host1, camera_d1 = func(
-print(device_ts1)
+    device_host1, sorted(list(camera_ts_map.keys())))
 
-print(a1-a0, (device_ts1-device_ts0)*10**3, int((r1-r0)*10**9))
+seq, encoder, host_ts, device_deivce0, buffer = b2t(
-print((a1-a0-(device_ts1-device_ts0)*10**3)*10**-9)
+    device_ts_map[device_host0].read_bytes())
-print((a1-a0-int((r1-r0)*10**9))*10**-9)
+device_deivce0 *= 10**3
+seq, encoder, host_ts, device_deivce1, buffer = b2t(
+    device_ts_map[device_host1].read_bytes())
+device_deivce1 *= 10**3
+
+device_host_diff = device_host1-device_host0
+device_deivce_diff = device_deivce1-device_deivce0
+robot_device_diff = robot_device1-robot_device0
+camera_host_diff = camera_host1 - camera_host0
+
+print(robot_d0/10**9, robot_d1/10**9)
+print(camera_d0/10**9, camera_d1/10**9)
+
+print('device_host_diff', device_host_diff/10**9)
+print('device_deivce_diff', device_deivce_diff/10**9)
+print('robot_device_diff', robot_device_diff/10**9)
+print('camera_host_diff', camera_host_diff/10**9)
+
+print('device_host - device_deivce', (device_host_diff-device_deivce_diff)/10**9)
+print('device_host - robot_device', (device_host_diff-robot_device_diff)/10**9)
+print('device_host - camera_host', (device_host_diff-camera_host_diff)/10**9)
+print('device_deivce - robot_device',
+      (device_deivce_diff-robot_device_diff)/10**9)
+
+
+x = np.array(list(device_ts_map.keys()))
+y = np.zeros_like(x)
+plt.scatter(x, y)
+
+x = np.array(list(robot_ts_map.keys()))
+y = np.zeros_like(x)+1
+plt.scatter(x, y)
+
+x = np.array(list(camera_ts_map.keys()))
+y = np.zeros_like(x)+2
+plt.scatter(x, y)
+plt.show()
 
 # for i, a in enumerate(ass):
 

test/sync_time_prepare.py

@@ -0,0 +1,52 @@
+from flandre.utils.RfFrame import b2t
+import json
+from pathlib import Path
+import itertools
+
+import cv2
+import numpy as np
+from nvidia import nvimgcodec
+decoder = nvimgcodec.Decoder()
+encoder = nvimgcodec.Encoder()
+
+
+rec_folder = Path(
+    '/run/media/lambda/b86dccdc-f134-464b-a310-6575ee9ae85c/record2/')
+
+robot_folder = rec_folder / 'robot'
+robot_folder = rec_folder / 'robot'
+
+d: dict[int, dict] = dict()
+for file in robot_folder.glob('*'):
+    for line in file.read_text().splitlines():
+        s = line.split(',')
+        v = dict(
+            host_ts=int(s[0]),
+            device_ts=int(float(s[1])*10**9),
+            x=float(s[2]),
+            y=float(s[3]),
+            z=float(s[4]),
+            rx=float(s[5]),
+            ry=float(s[6]),
+            rz=float(s[7]),
+            fx=float(s[8]),
+            fy=float(s[9]),
+            fz=float(s[10]),
+            frx=float(s[11]),
+            fry=float(s[12]),
+            frz=float(s[13]),
+        )
+        d[v['host_ts']] = v
+(rec_folder/'robot.json').write_text(json.dumps(d))
+
+for file in Path('/run/media/lambda/b86dccdc-f134-464b-a310-6575ee9ae85c/record2/camera_raw').glob('*.bin'):
+    fb = Path(file).read_bytes()
+    b = np.frombuffer(fb, dtype=np.uint8).reshape(
+        (1080, 1920, 3))
+    b = cv2.cvtColor(b, cv2.COLOR_BGR2RGB)
+    # cv2.imshow('',)
+    # cv2.waitKey(0)
+    # enc_params = nvimgcodec.EncodeParams(quality=5, chroma_subsampling=nvimgcodec.ChromaSubsampling.CSS_GRAY)
+    # encoder.write('a.jpg', b, params=enc_params)
+    encoder.write((file.parent.parent/'camera' /
+                  file.with_suffix('.jpg').name).__str__(), b)

uv.lock

@@ -501,6 +501,11 @@ dependencies = [
     { name = "zstd" },
 ]
 
+[package.optional-dependencies]
+to = [
+    { name = "nvidia-nvimgcodec-cu12" },
+]
+
 [package.metadata]
 requires-dist = [
     { name = "click", specifier = ">=8.1.8" },
@@ -509,6 +514,7 @@ requires-dist = [
     { name = "jupyter", specifier = ">=1.1.1" },
     { name = "matplotlib", specifier = ">=3.10.1" },
     { name = "mido", extras = ["ports-rtmidi"], specifier = ">=1.3.3" },
+    { name = "nvidia-nvimgcodec-cu12", marker = "extra == 'to'", specifier = ">=0.5.0.13" },
     { name = "opencv-python", specifier = ">=4.10.0.84" },
     { name = "platformdirs", specifier = ">=4.3.6" },
     { name = "pyjoystick", specifier = ">=1.2.4" },
@@ -520,6 +526,7 @@ requires-dist = [
     { name = "websockets", specifier = ">=15.0.1" },
     { name = "zstd", specifier = ">=1.5.6.7" },
 ]
+provides-extras = ["to"]
 
 [[package]]
 name = "fonttools"
@@ -1222,6 +1229,16 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/89/ea/00537f599eb230771157bc509f6ea5b2dddf05d4b09f9d2f1d7096a18781/numpy-2.2.0-cp312-cp312-win_amd64.whl", hash = "sha256:3a4199f519e57d517ebd48cb76b36c82da0360781c6a0353e64c0cac30ecaad3", size = 12613227, upload-time = "2024-12-08T15:32:34.792Z" },
 ]
 
+[[package]]
+name = "nvidia-nvimgcodec-cu12"
+version = "0.5.0.13"
+source = { registry = "https://pypi.org/simple" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/28/9a/f6c9105cb045f52af2096417ce92e7e8fba4d24ffe24d2cc82eb9bbe5534/nvidia_nvimgcodec_cu12-0.5.0.13-py3-none-manylinux2014_aarch64.whl", hash = "sha256:d76fadc2ed0f9075871627e45f2592c7807a0e944a0505afc21f87ccceb75caa", size = 17967646, upload-time = "2025-03-18T10:40:26.76Z" },
+    { url = "https://files.pythonhosted.org/packages/f0/6d/1c9919912ee97a4f52674f1c2deec7ab80df8fdd9a8b76f8ed4d75ebf799/nvidia_nvimgcodec_cu12-0.5.0.13-py3-none-manylinux2014_x86_64.whl", hash = "sha256:24cf0a759b1b02a6c3c0aedf8bf6602643f74c4c6df68c4b1c3c4ec1d48d71b0", size = 23304465, upload-time = "2025-03-18T10:40:54.19Z" },
+    { url = "https://files.pythonhosted.org/packages/3b/a8/58243c8f855b29116b1da9ee222b1afeb6a18a2120e66a0af2f85bee13ac/nvidia_nvimgcodec_cu12-0.5.0.13-py3-none-win_amd64.whl", hash = "sha256:331fc77cc844b982ab0d5c0e9d660b2e777e82c61471657c18f40ca3d15640c2", size = 27621245, upload-time = "2025-03-18T10:38:26.251Z" },
+]
+
 [[package]]
 name = "opencv-python"
 version = "4.10.0.84"