Experiment with separate renderer for actual projection

trap/animation_renderer.py

@@ -0,0 +1,427 @@
+# used for "Forward Referencing of type annotations"
+from __future__ import annotations
+
+import time
+import ffmpeg
+from argparse import Namespace
+import datetime
+import logging
+from multiprocessing import Event
+from multiprocessing.synchronize import Event as BaseEvent
+import cv2
+import numpy as np
+
+import pyglet
+import pyglet.event
+import zmq
+import tempfile
+from pathlib import Path
+import shutil
+import math
+
+from pyglet import shapes
+from PIL import Image
+
+from trap.frame_emitter import DetectionState, Frame, Track
+from trap.preview_renderer import DrawnTrack, PROJECTION_IMG, PROJECTION_MAP
+
+
+logger = logging.getLogger("trap.renderer")
+
+class AnimationRenderer:
+    def __init__(self, config: Namespace, is_running: BaseEvent):
+        self.config = config
+        self.is_running = is_running
+
+        context = zmq.Context()
+        self.prediction_sock = context.socket(zmq.SUB)
+        self.prediction_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
+        self.prediction_sock.setsockopt(zmq.SUBSCRIBE, b'')
+        self.prediction_sock.connect(config.zmq_prediction_addr if not self.config.bypass_prediction else config.zmq_trajectory_addr)
+        
+        self.tracker_sock = context.socket(zmq.SUB)
+        self.tracker_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
+        self.tracker_sock.setsockopt(zmq.SUBSCRIBE, b'')
+        self.tracker_sock.connect(config.zmq_trajectory_addr)
+        
+        self.frame_sock = context.socket(zmq.SUB)
+        self.frame_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
+        self.frame_sock.setsockopt(zmq.SUBSCRIBE, b'')
+        self.frame_sock.connect(config.zmq_frame_addr)
+    
+        self.H = self.config.H
+
+        self.inv_H = np.linalg.pinv(self.H)
+
+        # TODO: get FPS from frame_emitter
+        # self.out = cv2.VideoWriter(str(filename), fourcc, 23.97, (1280,720))
+        self.fps = 60
+        self.frame_size = (self.config.frame_width,self.config.frame_height)
+        self.hide_stats = False
+        self.out_writer = None # self.start_writer() if self.config.render_file else None
+        self.streaming_process = None # self.start_streaming() if self.config.render_url else None
+
+        if self.config.render_window:
+            pass          
+            # cv2.namedWindow("frame", cv2.WND_PROP_FULLSCREEN)
+            # cv2.setWindowProperty("frame",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
+        else:
+            pyglet.options["headless"] = True
+        
+        config = pyglet.gl.Config(sample_buffers=1, samples=4)
+        # , fullscreen=self.config.render_window
+        self.window = pyglet.window.Window(width=self.frame_size[0], height=self.frame_size[1], config=config, fullscreen=self.config.full_screen)
+        self.window.set_handler('on_draw', self.on_draw)
+        self.window.set_handler('on_refresh', self.on_refresh)
+        self.window.set_handler('on_close', self.on_close)
+
+        pyglet.gl.glClearColor(0,0,0, 0)
+        self.fps_display = pyglet.window.FPSDisplay(window=self.window, color=(255,255,255,255))
+        self.fps_display.label.x = self.window.width - 50
+        self.fps_display.label.y = self.window.height - 17
+        self.fps_display.label.bold = False
+        self.fps_display.label.font_size = 10
+
+        self.drawn_tracks: dict[str, DrawnTrack] = {}
+
+
+        self.first_time: float|None = None
+        self.frame: Frame|None= None
+        self.tracker_frame: Frame|None = None
+        self.prediction_frame: Frame|None = None
+
+
+        self.batch_bg = pyglet.graphics.Batch()
+        self.batch_overlay = pyglet.graphics.Batch()
+        self.batch_anim = pyglet.graphics.Batch()
+        
+        self.init_shapes()
+
+        self.init_labels()
+
+    
+    def init_shapes(self):
+        '''
+        Due to error when running headless, we need to configure options before extending the shapes class
+        '''
+        class GradientLine(shapes.Line):
+            def __init__(self, x, y, x2, y2, width=1, color1=[255,255,255], color2=[255,255,255], batch=None, group=None):
+                # print('colors!', colors)
+                # assert len(colors) == 6
+                
+                r, g, b, *a = color1
+                self._rgba1 = (r, g, b, a[0] if a else 255)
+                r, g, b, *a = color2
+                self._rgba2 = (r, g, b, a[0] if a else 255)
+                
+                # print('rgba', self._rgba)
+
+                super().__init__(x, y, x2, y2, width, color1, batch=None, group=None)
+                # <pyglet.graphics.vertexdomain.VertexList
+                # pyglet.graphics.vertexdomain
+                # print(self._vertex_list)
+            
+            def _create_vertex_list(self):
+                '''
+                copy of super()._create_vertex_list but with additional colors'''
+                self._vertex_list = self._group.program.vertex_list(
+                    6, self._draw_mode, self._batch, self._group,
+                    position=('f', self._get_vertices()),
+                    colors=('Bn', self._rgba1+ self._rgba2 + self._rgba2 + self._rgba1 + self._rgba2 +self._rgba1 ),
+                    translation=('f', (self._x, self._y) * self._num_verts))
+            
+            def _update_colors(self):
+                self._vertex_list.colors[:] = self._rgba1+ self._rgba2 + self._rgba2 + self._rgba1 + self._rgba2 +self._rgba1
+            
+            def color1(self, color):
+                r, g, b, *a = color
+                self._rgba1 = (r, g, b, a[0] if a else 255)
+                self._update_colors()
+            
+            def color2(self, color):
+                r, g, b, *a = color
+                self._rgba2 = (r, g, b, a[0] if a else 255)
+                self._update_colors()
+                
+        self.gradientLine = GradientLine
+
+    def init_labels(self):
+        base_color = (255,)*4
+        color_predictor = (255,255,0, 255)
+        color_info = (255,0, 255, 255)
+        color_tracker = (0,255, 255, 255)
+
+        options = []
+        for option in ['prediction_horizon','num_samples','full_dist','gmm_mode','z_mode', 'model_dir']:
+            options.append(f"{option}: {self.config.__dict__[option]}")
+
+        self.labels = {
+            'waiting': pyglet.text.Label("Waiting for prediction"),
+            'frame_idx': pyglet.text.Label("", x=20, y=self.window.height - 17, color=base_color, batch=self.batch_overlay),
+            'tracker_idx': pyglet.text.Label("", x=90, y=self.window.height - 17, color=color_tracker, batch=self.batch_overlay),
+            'pred_idx': pyglet.text.Label("", x=110, y=self.window.height - 17, color=color_predictor, batch=self.batch_overlay),
+            'frame_time': pyglet.text.Label("t", x=140, y=self.window.height - 17, color=base_color, batch=self.batch_overlay),
+            'frame_latency': pyglet.text.Label("", x=235, y=self.window.height - 17, color=color_info, batch=self.batch_overlay),
+            'tracker_time': pyglet.text.Label("", x=300, y=self.window.height - 17, color=color_tracker, batch=self.batch_overlay),
+            'pred_time': pyglet.text.Label("", x=360, y=self.window.height - 17, color=color_predictor, batch=self.batch_overlay),
+            'track_len': pyglet.text.Label("", x=800, y=self.window.height - 17, color=color_tracker, batch=self.batch_overlay),
+            'options1': pyglet.text.Label(options.pop(-1), x=20, y=30, color=base_color, batch=self.batch_overlay),
+            'options2': pyglet.text.Label(" | ".join(options), x=20, y=10, color=base_color, batch=self.batch_overlay),
+        }
+    
+    def refresh_labels(self, dt: float):
+        """Every frame"""
+        
+        if self.frame:
+            self.labels['frame_idx'].text = f"{self.frame.index:06d}"
+            self.labels['frame_time'].text = f"{self.frame.time - self.first_time: >10.2f}s"
+            self.labels['frame_latency'].text = f"{self.frame.time - time.time():.2f}s"
+        
+        if self.tracker_frame:
+            self.labels['tracker_idx'].text = f"{self.tracker_frame.index - self.frame.index}"
+            self.labels['tracker_time'].text = f"{self.tracker_frame.time - time.time():.3f}s"
+            self.labels['track_len'].text = f"{len(self.tracker_frame.tracks)} tracks"
+        
+        if self.prediction_frame:
+            self.labels['pred_idx'].text = f"{self.prediction_frame.index - self.frame.index}"
+            self.labels['pred_time'].text = f"{self.prediction_frame.time - time.time():.3f}s"
+            # self.labels['track_len'].text = f"{len(self.prediction_frame.tracks)} tracks"
+
+
+        # cv2.putText(img, f"{frame.index:06d}", (20,17), cv2.FONT_HERSHEY_PLAIN, 1, base_color, 1)
+        # cv2.putText(img, f"{frame.time - first_time:.3f}s", (120,17), cv2.FONT_HERSHEY_PLAIN, 1, base_color, 1)
+
+        # if prediction_frame:
+        #     # render Δt and Δ frames
+        #     cv2.putText(img, f"{prediction_frame.index - frame.index}", (90,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
+        #     cv2.putText(img, f"{prediction_frame.time - time.time():.2f}s", (200,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
+        #     cv2.putText(img, f"{len(prediction_frame.tracks)} tracks", (500,17), cv2.FONT_HERSHEY_PLAIN, 1, base_color, 1)
+        #     cv2.putText(img, f"h: {np.average([len(t.history or []) for t in prediction_frame.tracks.values()]):.2f}", (580,17),  cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
+        #     cv2.putText(img, f"ph: {np.average([len(t.predictor_history or []) for t in prediction_frame.tracks.values()]):.2f}", (660,17),  cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
+        #     cv2.putText(img, f"p: {np.average([len(t.predictions or []) for t in prediction_frame.tracks.values()]):.2f}", (740,17),  cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
+        
+        # options = []
+        # for option in ['prediction_horizon','num_samples','full_dist','gmm_mode','z_mode', 'model_dir']:
+        #     options.append(f"{option}: {config.__dict__[option]}")
+        
+
+        # cv2.putText(img, options.pop(-1), (20,img.shape[0]-30),  cv2.FONT_HERSHEY_PLAIN, 1, base_color, 1)
+        # cv2.putText(img, " | ".join(options), (20,img.shape[0]-10),  cv2.FONT_HERSHEY_PLAIN, 1, base_color, 1)
+
+        
+
+    def check_frames(self, dt):
+        new_tracks = False
+        try:
+            self.frame: Frame = self.frame_sock.recv_pyobj(zmq.NOBLOCK)
+            if not self.first_time:
+                self.first_time = self.frame.time
+            img = self.frame.img
+            img = cv2.warpPerspective(img, self.H, (self.frame.img.shape[1], self.frame.img.shape[0]))
+            img = cv2.GaussianBlur(img, (15, 15), 0)
+            img = cv2.flip(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), 0)
+            img = pyglet.image.ImageData(self.frame_size[0], self.frame_size[1], 'RGB', img.tobytes())
+            # don't draw in batch, so that it is the background
+            self.video_sprite = pyglet.sprite.Sprite(img=img, batch=self.batch_bg)
+            self.video_sprite.opacity = 100
+        except zmq.ZMQError as e:
+            # idx = frame.index if frame else "NONE"
+            # logger.debug(f"reuse video frame {idx}")
+            pass
+        try:
+            self.prediction_frame: Frame = self.prediction_sock.recv_pyobj(zmq.NOBLOCK)
+            new_tracks = True
+        except zmq.ZMQError as e:
+            pass
+        try:
+            self.tracker_frame: Frame = self.tracker_sock.recv_pyobj(zmq.NOBLOCK)
+            new_tracks = True
+        except zmq.ZMQError as e:
+            pass
+        
+        if new_tracks:
+            self.update_tracks()
+
+    def update_tracks(self):
+        """Updates the track objects and shapes. Called after setting `prediction_frame`
+        """
+        
+        # clean up
+        # for track_id in list(self.drawn_tracks.keys()):
+        #     if track_id not in self.prediction_frame.tracks.keys():
+        #         # TODO fade out
+        #         del self.drawn_tracks[track_id]
+        
+        if self.prediction_frame:
+            for track_id, track in self.prediction_frame.tracks.items():
+                if track_id not in self.drawn_tracks:
+                    self.drawn_tracks[track_id] = DrawnTrack(track_id, track, self, self.prediction_frame.H, PROJECTION_MAP)
+                else:
+                    self.drawn_tracks[track_id].set_track(track, self.prediction_frame.H)
+        
+        # clean up
+        for track_id in list(self.drawn_tracks.keys()):
+            # TODO make delay configurable
+            if self.drawn_tracks[track_id].update_at < time.time() - 5:
+                # TODO fade out
+                del self.drawn_tracks[track_id]
+
+    
+    def on_key_press(self, symbol, modifiers):
+        print('A key was pressed, use f to hide')
+        if symbol == ord('f'):
+            self.window.set_fullscreen(not self.window.fullscreen)
+        if symbol == ord('h'):
+            self.hide_stats = not self.hide_stats
+    
+    def check_running(self, dt):
+        if not self.is_running.is_set():
+            self.window.close()
+            self.event_loop.exit()
+    
+    def on_close(self):
+        self.is_running.clear()
+    
+    def on_refresh(self, dt: float):
+        # update shapes
+        # self.bg =
+        for track_id, track in self.drawn_tracks.items():
+            track.update_drawn_positions(dt)
+
+
+        self.refresh_labels(dt)
+
+        # self.shape1 = shapes.Circle(700, 150, 100, color=(50, 0, 30), batch=self.batch_anim)
+        # self.shape3 = shapes.Circle(800, 150, 100, color=(100, 225, 30), batch=self.batch_anim)
+        pass
+    
+    def on_draw(self):
+        self.window.clear()
+
+        self.batch_bg.draw()
+        
+        for track in self.drawn_tracks.values():
+            for shape in track.shapes:
+                shape.draw() # for some reason the batches don't work
+        for track in self.drawn_tracks.values():
+            for shapes in track.pred_shapes:
+                for shape in shapes:
+                    shape.draw()
+        # self.batch_anim.draw()
+        self.batch_overlay.draw()
+        
+
+        # pyglet.graphics.draw(3, pyglet.gl.GL_LINE, ("v2i", (100,200, 600,800)), ('c3B', (255,255,255, 255,255,255)))
+
+
+
+        if not self.hide_stats:
+            self.fps_display.draw()
+
+        # if streaming, capture buffer and send
+        try:
+            if self.streaming_process or self.out_writer:
+                buf = pyglet.image.get_buffer_manager().get_color_buffer()
+                img_data = buf.get_image_data()
+                data = img_data.get_data() # alternative: .get_data("RGBA", image_data.pitch)
+                img = np.asanyarray(data).reshape((img_data.height, img_data.width, 4))
+                img = cv2.cvtColor(img, cv2.COLOR_BGRA2RGB)
+                img = np.flip(img, 0)
+                # img = cv2.flip(img, cv2.0)
+
+                # cv2.imshow('frame', img)
+                # cv2.waitKey(1)
+                if self.streaming_process:
+                    self.streaming_process.stdin.write(img.tobytes())
+                if self.out_writer:
+                    self.out_writer.write(img)
+        except Exception as e:
+            logger.exception(e)
+
+
+            
+    def run(self):
+        frame = None
+        prediction_frame = None
+        tracker_frame = None
+
+        i=0
+        first_time = None
+
+        self.event_loop = pyglet.app.EventLoop()
+        pyglet.clock.schedule_interval(self.check_running, 0.1)
+        pyglet.clock.schedule(self.check_frames)
+        self.event_loop.run()
+        
+        
+
+        # while self.is_running.is_set():
+        #     i+=1
+
+
+        #     # zmq_ev = self.frame_sock.poll(timeout=2000)
+        #     # if not zmq_ev:
+        #     #     # when no data comes in, loop so that is_running is checked
+        #     #     continue
+        
+        #     try:
+        #         frame: Frame = self.frame_sock.recv_pyobj(zmq.NOBLOCK)
+        #     except zmq.ZMQError as e:
+        #         # idx = frame.index if frame else "NONE"
+        #         # logger.debug(f"reuse video frame {idx}")
+        #         pass
+        #     # else:
+        #     #     logger.debug(f'new video frame  {frame.index}')
+
+            
+        #     if frame is None:
+        #         # might need to wait a few iterations before first frame comes available
+        #         time.sleep(.1)
+        #         continue
+            
+        #     try:
+        #         prediction_frame: Frame = self.prediction_sock.recv_pyobj(zmq.NOBLOCK)
+        #     except zmq.ZMQError as e:
+        #         logger.debug(f'reuse prediction')
+
+        #     if first_time is None:
+        #             first_time = frame.time
+
+        #     img = decorate_frame(frame, prediction_frame, first_time, self.config)
+
+        #     img_path = (self.config.output_dir / f"{i:05d}.png").resolve()
+
+        #     logger.debug(f"write frame {frame.time - first_time:.3f}s")
+        #     if self.out_writer:
+        #         self.out_writer.write(img)
+        #     if self.streaming_process:
+        #         self.streaming_process.stdin.write(img.tobytes())
+        #     if self.config.render_window:
+        #         cv2.imshow('frame',img)
+        #         cv2.waitKey(1)
+        logger.info('Stopping')
+
+        # if i>2:
+        if self.streaming_process:
+            self.streaming_process.stdin.close()
+        if self.out_writer:
+            self.out_writer.release() 
+        if self.streaming_process:
+            # oddly wrapped, because both close and release() take time.
+            self.streaming_process.wait()
+
+# colorset = itertools.product([0,255], repeat=3) # but remove white
+colorset = [(0, 0, 0),
+ (0, 0, 255),
+ (0, 255, 0),
+ (0, 255, 255),
+ (255, 0, 0),
+ (255, 0, 255),
+ (255, 255, 0)
+ ]
+
+
+    
+def run_animation_renderer(config: Namespace, is_running: BaseEvent):
+    renderer = AnimationRenderer(config, is_running)
+    renderer.run()

trap/config.py

@@ -1,6 +1,8 @@
 import argparse
 from pathlib import Path
 import types
+import numpy as np
+import json
 
 from trap.tracker import DETECTORS
 
@@ -49,6 +51,21 @@ frame_emitter_parser = parser.add_argument_group('Frame emitter')
 tracker_parser = parser.add_argument_group('Tracker')
 render_parser = parser.add_argument_group('Renderer')
 
+class HomographyAction(argparse.Action):
+     def __init__(self, option_strings, dest, nargs=None, **kwargs):
+         if nargs is not None:
+             raise ValueError("nargs not allowed")
+         super().__init__(option_strings, dest, **kwargs)
+     def __call__(self, parser, namespace, values: Path, option_string=None):
+        if values.suffix == '.json':
+            with values.open('r') as fp:
+                H = np.array(json.load(fp))
+        else:
+            H = np.loadtxt(values, delimiter=',')
+        print('%r %r %r' % (namespace, values, option_string))
+        setattr(namespace, self.dest, values)
+        setattr(namespace, 'H', H)
+
 inference_parser.add_argument("--model_dir",
                     help="directory with the model to use for inference",
                     type=str, # TODO: make into Path
@@ -234,7 +251,8 @@ frame_emitter_parser.add_argument("--video-loop",
 tracker_parser.add_argument("--homography",
                     help="File with homography params",
                     type=Path,
-                    default='../DATASETS/VIRAT_subset_0102x/VIRAT_0102_homography_img2world.txt')
+                    default='../DATASETS/VIRAT_subset_0102x/VIRAT_0102_homography_img2world.txt',
+                    action=HomographyAction)
 tracker_parser.add_argument("--save-for-training",
                     help="Specify the path in which to save",
                     type=Path,
@@ -246,6 +264,15 @@ tracker_parser.add_argument("--detector",
 tracker_parser.add_argument("--smooth-tracks",
                     help="Smooth the tracker tracks before sending them to the predictor",
                     action='store_true')
+tracker_parser.add_argument("--frame-width",
+                    help="width of the frames",
+                    type=int,
+                    default=1280)
+tracker_parser.add_argument("--frame-height",
+                    help="height of the frames",
+                    type=int,
+                    default=720)
+
 
 # Renderer
 

trap/frame_emitter.py

@@ -85,7 +85,7 @@ class Track:
 
     def get_projected_history(self, H) -> np.array:
         foot_coordinates = [d.get_foot_coords() for d in self.history]
-        
+        # TODO)) Undistort points before perspective transform
         if len(foot_coordinates):
             coords = cv2.perspectiveTransform(np.array([foot_coordinates]),H)
             return coords[0]
@@ -151,8 +151,8 @@ class FrameEmitter:
                 # numeric input is a CV camera
                 video = cv2.VideoCapture(int(str(video_path)))
                 # TODO: make config variables
-                video.set(cv2.CAP_PROP_FRAME_WIDTH, int(1280))
+                video.set(cv2.CAP_PROP_FRAME_WIDTH, int(self.config.frame_width))
-                video.set(cv2.CAP_PROP_FRAME_HEIGHT, int(720))
+                video.set(cv2.CAP_PROP_FRAME_HEIGHT, int(self.config.frame_height))
                 print("exposure!", video.get(cv2.CAP_PROP_AUTO_EXPOSURE))
                 video.set(cv2.CAP_PROP_FPS, 5)
             else:

trap/plumber.py

@@ -9,7 +9,8 @@ import time
 from trap.config import parser
 from trap.frame_emitter import run_frame_emitter
 from trap.prediction_server import run_prediction_server
-from trap.renderer import run_renderer
+from trap.preview_renderer import run_preview_renderer
+from trap.animation_renderer import run_animation_renderer
 from trap.socket_forwarder import run_ws_forwarder
 from trap.tracker import run_tracker
 
@@ -75,7 +76,10 @@ def start():
     
     if args.render_file or args.render_url or args.render_window:
         procs.append(
-            ExceptionHandlingProcess(target=run_renderer, kwargs={'config': args, 'is_running': isRunning}, name='renderer')
+            ExceptionHandlingProcess(target=run_preview_renderer, kwargs={'config': args, 'is_running': isRunning}, name='renderer')
+        )
+        procs.append(
+            ExceptionHandlingProcess(target=run_animation_renderer, kwargs={'config': args, 'is_running': isRunning}, name='map_renderer')
         )
 
     if not args.bypass_prediction:

trap/preview_renderer.py

@@ -10,7 +10,7 @@ from multiprocessing import Event
 from multiprocessing.synchronize import Event as BaseEvent
 import cv2
 import numpy as np
-
+import json
 import pyglet
 import pyglet.event
 import zmq
@@ -26,7 +26,7 @@ from trap.frame_emitter import DetectionState, Frame, Track
 
 
 
-logger = logging.getLogger("trap.renderer")
+logger = logging.getLogger("trap.preview")
 
 class FrameAnimation:
     def __init__(self, frame: Frame):
@@ -55,10 +55,15 @@ def relativePointToPolar(origin, point) -> tuple[float, float]:
 def relativePolarToPoint(origin, r, angle) -> tuple[float, float]:
     return r * np.cos(angle) + origin[0], r * np.sin(angle) + origin[1]
 
+PROJECTION_IMG = 0
+PROJECTION_UNDISTORT = 1
+PROJECTION_MAP = 2
+PROJECTION_PROJECTOR = 4
 
 class DrawnTrack:
-    def __init__(self, track_id, track: Track, renderer: Renderer, H):
+    def __init__(self, track_id, track: Track, renderer: PreviewRenderer, H, draw_projection = PROJECTION_IMG):
         # self.created_at = time.time()
+        self.draw_projection = draw_projection
         self.update_at = self.created_at = time.time()
         self.track_id = track_id
         self.renderer = renderer
@@ -73,14 +78,17 @@ class DrawnTrack:
 
         self.track = track
         self.H = H
-        self.coords = [d.get_foot_coords() for d in track.history]
+        self.coords = [d.get_foot_coords() for d in track.history] if self.draw_projection == PROJECTION_IMG else track.get_projected_history(self.H)
 
         # perhaps only do in constructor:
         self.inv_H = np.linalg.pinv(self.H)
 
         pred_coords = []
+        if self.draw_projection == PROJECTION_IMG:
             for pred_i, pred in enumerate(track.predictions):
                 pred_coords.append(cv2.perspectiveTransform(np.array([pred]), self.inv_H)[0].tolist())
+        elif self.draw_projection == PROJECTION_MAP:
+            pred_coords = [pred for pred in track.predictions]
         
         self.pred_coords = pred_coords
             # color = (128,0,128) if pred_i else (128,
@@ -232,7 +240,7 @@ class FrameWriter:
         
 
 
-class Renderer:
+class PreviewRenderer:
     def __init__(self, config: Namespace, is_running: BaseEvent):
         self.config = config
         self.is_running = is_running
@@ -253,14 +261,23 @@ class Renderer:
         self.frame_sock.setsockopt(zmq.SUBSCRIBE, b'')
         self.frame_sock.connect(config.zmq_frame_addr)
     
-        self.H = np.loadtxt(self.config.homography, delimiter=',')
+        
+        # TODO)) Move loading H to config.py
+        # if self.config.homography.suffix == '.json':
+        #     with self.config.homography.open('r') as fp:
+        #         self.H = np.array(json.load(fp))
+        # else:
+        #     self.H = np.loadtxt(self.config.homography, delimiter=',')
+        print('h', self.config.H)
+        self.H = self.config.H
+            
 
         self.inv_H = np.linalg.pinv(self.H)
 
         # TODO: get FPS from frame_emitter
         # self.out = cv2.VideoWriter(str(filename), fourcc, 23.97, (1280,720))
         self.fps = 60
-        self.frame_size = (1280,720)
+        self.frame_size = (self.config.frame_width,self.config.frame_height)
         self.hide_stats = False
         self.out_writer = self.start_writer() if self.config.render_file else None
         self.streaming_process = self.start_streaming() if self.config.render_url else None
@@ -772,6 +789,6 @@ def decorate_frame(frame: Frame, prediction_frame: Frame, first_time: float, con
     return img
 
     
-def run_renderer(config: Namespace, is_running: BaseEvent):
+def run_preview_renderer(config: Namespace, is_running: BaseEvent):
-    renderer = Renderer(config, is_running)
+    renderer = PreviewRenderer(config, is_running)
     renderer.run()

trap/tracker.py

@@ -105,7 +105,7 @@ class Tracker:
 
         # homography = list(source.glob('*img2world.txt'))[0]
 
-        self.H = np.loadtxt(self.config.homography, delimiter=',')
+        self.H = self.config.H
 
         if self.config.smooth_tracks:
             logger.info("Smoother enabled")