ref: create vision_chunk

main.py

@@ -1,9 +1,11 @@
-from simulator import Simulator
-from visualization import VisualizationManager
-from trajectory_drawer import TrajectoryDrawer
-from yandex_map import YandexMap
-from time import sleep
 from pathlib import Path
+from simulator import Simulator
+from time import sleep
+from trajectory_drawer import TrajectoryDrawer
+from visualization import VisualizationManager
+from yandex_map import YandexMap
+from vision_chunk import VisionChunk
+from utility import cv2_to_pil
 import random
 
 import cv2
@@ -37,16 +39,18 @@ def main():
 
     # Для каждой точки сделаем приближенный снимок
     yandexMap = YandexMap()
-    keypoints: list[(any, any)] = []
+    chunks: list[VisionChunk] = []
 
     plt.ion()
     for i in range(len(points)):
         point = points[i]
         yandexMap.scroll(point[0], point[1], 5, True)
         sleep(1)
-        img = yandexMap.make_screenshot(point[0], point[1], 0.2, 0.2)
+        cv2_img = yandexMap.make_screenshot(point[0], point[1], 0.2, 0.2)
+        img = cv2_to_pil(cv2_img)
+        chunk = VisionChunk(img)
         Path('chunks').mkdir(exist_ok=True)
-        cv2.imwrite(Path('.') / 'chunks' / f'chunk_{i}.png', img)
+        chunk.save_image(Path('.') / 'chunks' / f'chunk_{i}.png')
         plt.subplot(1, len(points), i+1)
         plt.imshow(img)
         plt.pause(0.25)
@@ -56,20 +60,9 @@ def main():
 
     # Выделим на каждой картинке ключевые точки
     for i in range(len(points)):
-        orb = cv2.ORB_create(
-            nfeatures=1000,
-            scaleFactor=1.2,
-            nlevels=8,
-            edgeThreshold=31,
-            firstLevel=0,
-            WTA_K=2,
-            patchSize=31,
-            fastThreshold=20
-        )
-        img = cv2.imread(Path('chunks') / f'chunk_{i}.png')
-        kp: list[cv2.KeyPoint]
-        kp, des = orb.detectAndCompute(img, None)
-        keypoints.append((kp, des))
+        chunk = VisionChunk.load_image(Path('chunks') / f'chunk_{i}.png')
+        chunks.append(chunk)
+        kp, des = chunk.compute_keypoints()
 
         plt.subplot(1, len(points), i+1)
         kp_coords = np.array([j.pt for j in kp])
@@ -93,12 +86,12 @@ def main():
             (p[0] - points[0][0]) * width, (points[0][1] - p[1]) * height
         ], points)))
     points_coords *= 2 ** 4
-    pilot = autopilot.AutoPilot(points_coords, keypoints, vis_manager)
+    pilot = autopilot.AutoPilot(points_coords, chunks, vis_manager)
     simulator = Simulator(yandexMap)
     pilot.target_idx = 0
 
-    photo = simulator.get_photo()
-    command = pilot.handle(photo)
+    chunk = simulator.get_chunk()
+    command = pilot.handle(chunk)
 
     vis_manager.update_display()
     vis_manager.pause(1)
@@ -117,13 +110,13 @@ def main():
             simulator.change_zoom(direction)
             zoom_next_event = i + random.randint(20, 40)
 
-        photo = simulator.get_photo()
-        command = pilot.handle(photo)
+        chunk = simulator.get_chunk()
+        command = pilot.handle(chunk)
 
         proc_time = np.append(proc_time, command.proccessing_time)
         
         # Save Image
-        photo.save(Path('images') / f"photo_{i}.png")
+        chunk.save_image(Path('images') / f"photo_{i}.png")
 
         vis_manager.update_display()
         vis_manager.pause(0.2)
@@ -142,7 +135,7 @@ def main():
         vis_manager.pause(0.2)
 
         last_proc_times = proc_time[-10:]
-        # print("Average FPS:", 1 / last_proc_times.mean())
+        print("Average FPS:", 1 / last_proc_times.mean())
 
     vis_manager.show_final()