Daniel Suzuki's Bootcamp

modules/bootcamp/decision_simple_waypoint.py

@@ -37,7 +37,7 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Add your own
+        self.halt_at_initialization = True
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
@@ -69,6 +69,22 @@ def run(
         # ============
 
         # Do something based on the report and the state of this class...
+        if report.status == drone_status.DroneStatus.HALTED:
+            if self.halt_at_initialization:
+                command = commands.Command.create_set_relative_destination_command(
+                    self.waypoint.location_x - report.position.location_x,
+                    self.waypoint.location_y - report.position.location_y,
+                )
+                self.halt_at_initialization = False
+            elif (
+                report.status == drone_status.DroneStatus.HALTED
+                and (
+                    (report.position.location_x - self.waypoint.location_x) ** 2
+                    + (report.position.location_y - self.waypoint.location_y) ** 2
+                )
+                <= self.acceptance_radius**2
+            ):
+                command = commands.Command.create_land_command()
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑

modules/bootcamp/decision_waypoint_landing_pads.py

@@ -36,12 +36,15 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
         # ============
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
+        # set as closest landing to waypoint
+        self.halt_at_initialization = True
+        self.is_halt_at_waypoint = False
+        self.closest_pad = location.Location(float("inf"), float("inf"))
 
-        # Add your own
-
-        # ============
-        # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
-        # ============
+    #  self.shortest_distance = [float("inf"), float("inf")]
+    # ============
+    # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
+    # ============
 
     def run(
         self, report: drone_report.DroneReport, landing_pad_locations: "list[location.Location]"
@@ -67,8 +70,53 @@ def run(
         # ============
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
+        def square(number: float) -> float:
+            return number**2
+
+        def squared_distance_from_position(
+            point: location.Location, current_position: location.Location
+        ) -> float:
+            distance = square(point.location_x - current_position.location_x) + (
+                square(point.location_y - current_position.location_y)
+            )
+            return distance
 
         # Do something based on the report and the state of this class...
+        if report.status == drone_status.DroneStatus.HALTED:
+            if self.halt_at_initialization:
+
+                command = commands.Command.create_set_relative_destination_command(
+                    self.waypoint.location_x - report.position.location_x,
+                    self.waypoint.location_y - report.position.location_y,
+                )
+                self.halt_at_initialization = False
+                self.is_halt_at_waypoint = True
+
+            elif self.is_halt_at_waypoint:
+                for landing_pad in landing_pad_locations:
+                    distance_from_position = squared_distance_from_position(
+                        landing_pad, self.waypoint
+                    )
+                    current_shortest_distance = squared_distance_from_position(
+                        self.closest_pad, report.position
+                    )
+                    # self.closest_pad.location_x - report.position.location_x
+                    #  ) ** 2 + (self.closest_pad.location_y - report.position.location_y) ** 2
+                    if distance_from_position < current_shortest_distance:
+                        self.closest_pad = landing_pad
+
+                command = commands.Command.create_set_relative_destination_command(
+                    self.closest_pad.location_x - report.position.location_x,
+                    self.closest_pad.location_y - report.position.location_y,
+                )
+                self.is_halt_at_waypoint = False
+
+            elif (
+                squared_distance_from_position(report.position, self.closest_pad)
+                <= self.acceptance_radius**2
+            ):
+
+                command = commands.Command.create_land_command()
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑

modules/bootcamp/detect_landing_pad.py

@@ -17,9 +17,7 @@
 # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
 # ============
 # Bootcampers remove the following lines:
-# Allow linters and formatters to pass for bootcamp maintainers
-# No enable
-# pylint: disable=unused-argument,unused-private-member,unused-variable
+#
 # ============
 # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
 # ============
@@ -98,31 +96,35 @@ def run(self, image: np.ndarray) -> "tuple[list[bounding_box.BoundingBox], np.nd
         # * conf
         # * device
         # * verbose
-        predictions = ...
+        predictions = self.__model.predict(image, conf=0.7, device=self.__DEVICE, verbose=True)
 
         # Get the Result object
-        prediction = ...
+        prediction = predictions[0]
 
         # Plot the annotated image from the Result object
         # Include the confidence value
-        image_annotated = ...
+        image_annotated = prediction.plot(conf=True)
 
         # Get the xyxy boxes list from the Boxes object in the Result object
-        boxes_xyxy = ...
+        boxes_xyxy = prediction.boxes.xyxy
 
         # Detach the xyxy boxes to make a copy,
         # move the copy into CPU space,
         # and convert to a numpy array
-        boxes_cpu = ...
+        boxes_cpu = boxes_xyxy.detach().cpu().numpy()
 
         # Loop over the boxes list and create a list of bounding boxes
         bounding_boxes = []
         # Hint: .shape gets the dimensions of the numpy array
         # for i in range(0, ...):
         #     # Create BoundingBox object and append to list
         #     result, box = ...
+        for i in range(0, boxes_cpu.shape[0]):
+            result, box = bounding_box.BoundingBox.create(boxes_cpu[i])
+            if result:
+                bounding_boxes.append(box)
 
-        return [], image_annotated
+        return bounding_boxes, image_annotated
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============

modules/bootcamp/tests/run_decision_example.py

@@ -21,7 +21,7 @@
 # to reach the 1st command
 # Increase the step size if your computer is lagging
 # Larger step size is smaller FPS
-TIME_STEP_SIZE = 0.1  # seconds
+TIME_STEP_SIZE = 0.7  # seconds
 
 # OpenCV ignores your display settings,
 # so if the window is too small or too large,

requirements.txt

@@ -17,7 +17,7 @@ pytest
 # If you are on MacOS, don't have a CUDA capable GPU,
 # or if things don't work and you just want to use the CPU,
 # comment out the "--extra-index-url" option
---extra-index-url https://download.pytorch.org/whl/cu124
+#--extra-index-url https://download.pytorch.org/whl/cu124
 
 # ============
 # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑