Migrate to uv

README.md

@@ -3,7 +3,7 @@
 ## Install
 
 * Run `bash build_opencv_with_gstreamer.sh` to build opencv with gstreamer support
-* Use pyenv + poetry to install
+* Use `uv` to install
 
 ## How to
 

pyproject.toml

@@ -1,11 +1,36 @@
-[tool.poetry]
+[project]
 name = "trap"
 version = "0.1.0"
 description = "Art installation with trajectory prediction"
-authors = ["Ruben van de Ven <git@rubenvandeven.com>"]
+authors = [{ name = "Ruben van de Ven", email = "git@rubenvandeven.com" }]
+requires-python = "~=3.10.4"
 readme = "README.md"
+dependencies = [
+    "trajectron-plus-plus",
+    "torch==1.12.1",
+    "torchvision==0.13.1",
+    "deep-sort-realtime>=1.3.2,<2",
+    "ultralytics~=8.3",
+    "ffmpeg-python>=0.2.0,<0.3",
+    "torchreid>=0.2.5,<0.3",
+    "gdown>=4.7.1,<5",
+    "pandas-helper-calc",
+    "tsmoothie>=1.0.5,<2",
+    "pyglet>=2.0.15,<3",
+    "pyglet-cornerpin>=0.3.0,<0.4",
+    "opencv-python",
+    "setproctitle>=1.3.3,<2",
+    "bytetracker",
+    "jsonlines>=4.0.0,<5",
+    "tensorboardx>=2.6.2.2,<3",
+    "shapely>=1,<2",
+    "baumer-neoapi",
+    "qrcode~=8.0",
+    "pyusb>=1.3.1,<2",
+    "ipywidgets>=8.1.5,<9",
+]
 
-[tool.poetry.scripts]
+[project.scripts]
 trapserv = "trap.plumber:start"
 tracker = "trap.tools:tracker_preprocess"
 compare = "trap.tools:tracker_compare"
@@ -13,42 +38,16 @@ process_data = "trap.process_data:main"
 blacklist = "trap.tools:blacklist_tracks"
 rewrite_tracks = "trap.tools:rewrite_raw_track_files"
 
-[tool.poetry.dependencies]
+[tool.uv]
-python = "^3.10,<3.12,"
 
-trajectron-plus-plus = { path = "../Trajectron-plus-plus/", develop = true }
+[tool.uv.sources]
-#trajectron-plus-plus = { git = "https://git.rubenvandeven.com/security_vision/Trajectron-plus-plus/" }
+trajectron-plus-plus = { path = "../Trajectron-plus-plus/", editable = true }
-torch = [
+torch = [{ url = "https://download.pytorch.org/whl/cu113/torch-1.12.1%2Bcu113-cp310-cp310-linux_x86_64.whl", marker = "python_version ~= '3.10' and sys_platform == 'linux'" }]
-        { version="1.12.1" },
+torchvision = [{ url = "https://download.pytorch.org/whl/cu113/torchvision-0.13.1%2Bcu113-cp310-cp310-linux_x86_64.whl", marker = "python_version ~= '3.10' and sys_platform == 'linux'" }]
-#       { url = "https://download.pytorch.org/whl/cu113/torch-1.12.1%2Bcu113-cp38-cp38-linux_x86_64.whl", markers = "python_version ~= '3.8' and sys_platform == 'linux'" },
+pandas-helper-calc = { git = "https://github.com/scls19fr/pandas-helper-calc" }
-        { url = "https://download.pytorch.org/whl/cu113/torch-1.12.1%2Bcu113-cp310-cp310-linux_x86_64.whl", markers = "python_version ~= '3.10' and sys_platform == 'linux'" },
+bytetracker = { git = "https://github.com/rubenvandeven/bytetrack-pip" }
-]
+baumer-neoapi = { path = "../../Downloads/Baumer_neoAPI_1.4.1_lin_x86_64_python/wheel/baumer_neoapi-1.4.1-cp34.cp35.cp36.cp37.cp38.cp39.cp310.cp311.cp312-none-linux_x86_64.whl" }
-
-torchvision = [
-       { version="0.13.1" },
-#       { url = "https://download.pytorch.org/whl/cu113/torchvision-0.13.1%2Bcu113-cp38-cp38-linux_x86_64.whl", markers = "python_version ~= '3.8' and sys_platform == 'linux'" },
-       { url = "https://download.pytorch.org/whl/cu113/torchvision-0.13.1%2Bcu113-cp310-cp310-linux_x86_64.whl", markers = "python_version ~= '3.10' and sys_platform == 'linux'" },
-]
-deep-sort-realtime = "^1.3.2"
-ultralytics = "^8.3"
-ffmpeg-python = "^0.2.0"
-torchreid = "^0.2.5"
-gdown = "^4.7.1"
-pandas-helper-calc = {git = "https://github.com/scls19fr/pandas-helper-calc"}
-tsmoothie = "^1.0.5"
-pyglet = "^2.0.15"
-pyglet-cornerpin = "^0.3.0"
-opencv-python = {file="./opencv_python-4.10.0.84-cp310-cp310-linux_x86_64.whl"}
-setproctitle = "^1.3.3"
-bytetracker =  { git = "https://github.com/rubenvandeven/bytetrack-pip" }
-jsonlines = "^4.0.0"
-tensorboardx = "^2.6.2.2"
-shapely = "^1"
-baumer-neoapi = {path = "../../Downloads/Baumer_neoAPI_1.4.1_lin_x86_64_python/wheel/baumer_neoapi-1.4.1-cp34.cp35.cp36.cp37.cp38.cp39.cp310.cp311.cp312-none-linux_x86_64.whl"}
-qrcode = "^8.0"
-pyusb = "^1.3.1"
-ipywidgets = "^8.1.5"
 
 [build-system]
-requires = ["poetry-core"]
+requires = ["hatchling"]
-build-backend = "poetry.core.masonry.api"
+build-backend = "hatchling.build"

trap/laser_renderer.py

@@ -70,6 +70,7 @@ class LaserFrame():
                 steps = int(distance // point_interval)
                 for step in range(steps+1): # have both 0 and 1 in the lerp for empty points
                     t = step/(steps+1)
+                    t = 1 # just asap to starting point of next shape
                     x = int(lerp(a.x, b.x, t))
                     y = int(lerp(a.y, b.y, t))
                     points.append(LaserPoint(x,y, (0,0,0), 0, True))
@@ -97,6 +98,58 @@ class LaserPath():
     def first(self):
         return self.points[0]
     
+    def as_array(self):
+        np.array([[p.x, p.y] for p in self.points])
+    
+    def simplyfied_path(self, start_v= 10., max_v= 20., a = 2):
+        """walk over the path with specific velocity,
+        continuously accelerate (a) until max_v is reached
+        place point at each step
+
+        (see also tools.transition_path_points() )
+        """
+        if len(self.points) < 1:
+            return self.points
+        
+        path = self.as_array()
+        
+        # new_path = np.array([])
+        lengths = np.sqrt(np.sum(np.diff(path, axis=0)**2, axis=1))
+        cum_lenghts = np.cumsum(lengths)
+        # distance = cum_lenghts[-1] * t
+        # ts = np.concatenate((np.array([0.]), cum_lenghts / cum_lenghts[-1]))
+        # print(cum_lenghts[-1])
+        # DRAW_SPEED = 35 # fixed speed (independent of lenght) TODO)) make variable
+        # ts = np.concatenate((np.array([0.]), cum_lenghts / DRAW_SPEED))
+        new_path = [path[0]]
+
+        position = 0
+        next_pos = position + v
+        
+        for a, b, pos in zip(path[:-1], path[1:], cum_lenghts):
+            # TODO))
+            if pos < (next_pos):
+                continue
+
+            v = min(v+a, max_v)
+            next_pos = position + v
+
+            relative_t = inv_lerp(t_a, t_b, t)
+
+            pass
+
+        # for a, b, t_a, t_b in zip(path[:-1], path[1:], ts[:-1], ts[1:]):
+        #     if t_b < t:
+        #         new_path.append(b)
+        #         continue
+        #     # interpolate
+        #     relative_t = inv_lerp(t_a, t_b, t)
+        #     x = lerp(a[0], b[0], relative_t)
+        #     y = lerp(a[1], b[1], relative_t)
+        #     new_path.append([x,y])
+        #     break
+        # return np.array(new_path)
+    
 class LaserPoint():
     def __init__(self,x,y,c: Color = (255,0,0),i= 255,blank=False):
         self.x = x
@@ -284,14 +337,18 @@ class LaserRenderer:
                     first_time = tracker_frame.time
 
             
-            paths = render_frame_to_pointlist( tracker_frame, prediction_frame, first_time, self.config, self.tracks, self.predictions, self.config.render_clusters)
+            # print('-------')
+            paths = render_frame_to_pathlist( tracker_frame, prediction_frame, first_time, self.config, self.tracks, self.predictions, self.config.render_clusters)
+            print(f"Paths: {len(paths)} ... points {sum([len(p.points) for p in paths])}")
             laserframe = LaserFrame(paths)
             # pointlist=pointlist_test
             # print([(p.x, p.y) for p in pointlist])
             # pointlist.extend(pointlist_test)
 
-            pointlist = laserframe.get_points_interpolated_by_distance(2, last_laser_point)
+            pointlist = laserframe.get_points_interpolated_by_distance(30, last_laser_point)
-            # print(len(pointlist))
+            print(len(pointlist))
+            # pointlist = pointlist[::2]
+            # print('decimated', len(pointlist))
 
             if len(pointlist):
                 last_laser_point = pointlist[-1] 
@@ -299,7 +356,7 @@ class LaserRenderer:
             frameType = CHeliosPoint * len(pointlist)
             frame = frameType()
 
-            # print(len(pointlist), last_laser_point.x, last_laser_point.y)
+            # print(len(pointlist)) #, last_laser_point.x, last_laser_point.y)
 
             for j, point in enumerate(pointlist):
                 frame[j] = CHeliosPoint(int(point.x), int(point.y), point.color[0],point.color[1], point.color[2], point.i)
@@ -363,7 +420,7 @@ def get_animation_position(track: Track, current_frame: Frame) -> float:
 
 def circle_points(cx, cy, r, c: Color):
     r = 100
-    steps = 100
+    steps = 30
     pointlist: list[LaserPoint] = []
     for i in range(steps):
         x = int(cx + math.cos(i * (2*math.pi)/steps) * r)
@@ -384,7 +441,7 @@ def world_points_to_laser_points(points):
     return cv2.perspectiveTransform(np.array([points]), laser_H)
 
 # Deprecated
-def render_frame_to_pointlist(tracker_frame: Optional[Frame], prediction_frame: Optional[Frame], first_time: Optional[float], config: Namespace, tracks: Dict[str, Track], predictions: Dict[str, Track], as_clusters = True):
+def render_frame_to_pathlist(tracker_frame: Optional[Frame], prediction_frame: Optional[Frame], first_time: Optional[float], config: Namespace, tracks: Dict[str, Track], predictions: Dict[str, Track], as_clusters = True):
     # TODO: replace opencv with QPainter to support alpha? https://doc.qt.io/qtforpython-5/PySide2/QtGui/QPainter.html#PySide2.QtGui.PySide2.QtGui.QPainter.drawImage
     # or https://github.com/pygobject/pycairo?tab=readme-ov-file
     # or https://pyglet.readthedocs.io/en/latest/programming_guide/shapes.html
@@ -444,6 +501,11 @@ def render_frame_to_pointlist(tracker_frame: Optional[Frame], prediction_frame:
             LaserPath(circle_points(0xFFF/2+2*test_r, 0xFFF/2, test_r, track_c))
             )
     else:
+        # if not len(tracks):
+        #     paths.append(
+        #     LaserPath(circle_points(0xFFF/2+4*test_r, 0xFFF/2, test_r/2, pred_c))
+        #     )
+
         for track_id, track in tracks.items():
             inv_H = np.linalg.pinv(tracker_frame.H)
             history = track.get_projected_history(camera=config.camera)