Lucas Kim's bootcamp

modules/bootcamp/decision_simple_waypoint.py

@@ -37,8 +37,6 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Add your own
-
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============
@@ -68,10 +66,32 @@ def run(
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Do something based on the report and the state of this class...
+        if report.status == drone_status.DroneStatus.HALTED:
+            allowed_error = self.acceptance_radius**2
+
+            # Check if the waypoint has already been reached
+            if self.__squared_distance(self.waypoint, report.position) < allowed_error:
+                command = commands.Command.create_land_command()
+            else:
+                relative_x = self.waypoint.location_x - report.position.location_x
+                relative_y = self.waypoint.location_y - report.position.location_y
+                command = commands.Command.create_set_relative_destination_command(
+                    relative_x, relative_y
+                )
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============
 
         return command
+
+    def __squared_distance(
+        self, location1: location.Location, location2: location.Location
+    ) -> float:
+        """
+        Calculate the distance between two Location objects.
+        """
+
+        return ((location2.location_x - location1.location_x) ** 2) + (
+            (location2.location_y - location1.location_y) ** 2
+        )

modules/bootcamp/decision_waypoint_landing_pads.py

@@ -13,7 +13,6 @@
 from .. import location
 from ..private.decision import base_decision
 
-
 # Disable for bootcamp use
 # No enable
 # pylint: disable=duplicate-code,unused-argument
@@ -37,7 +36,8 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Add your own
+        self.has_reached_waypoint = False
+        self.closest_landing_pad = None
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
@@ -68,10 +68,61 @@ def run(
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Do something based on the report and the state of this class...
+        if report.status == drone_status.DroneStatus.HALTED:
+            allowed_error = self.acceptance_radius**2
+
+            # Check if the landing pad or waypoint has already been reached
+            if self.has_reached_waypoint:
+                # Make sure the landing pad has actually been reached; otherwise send another set relative destination command
+                if (
+                    self.__squared_distance(report.position, self.closest_landing_pad)
+                    < allowed_error
+                ):
+                    command = commands.Command.create_land_command()
+                else:
+                    relative_x = self.closest_landing_pad.location_x - report.position.location_x
+                    relative_y = self.closest_landing_pad.location_y - report.position.location_y
+
+                    command = commands.Command.create_set_relative_destination_command(
+                        relative_x, relative_y
+                    )
+            elif self.__squared_distance(report.position, self.waypoint) < allowed_error:
+                self.closest_landing_pad = min(
+                    landing_pad_locations,
+                    key=lambda pad: self.__squared_distance(report.position, pad),
+                )
+
+                # Calculate relative x and y distance required to reach landing pad
+                relative_x = self.closest_landing_pad.location_x - report.position.location_x
+                relative_y = self.closest_landing_pad.location_y - report.position.location_y
+
+                command = commands.Command.create_set_relative_destination_command(
+                    relative_x, relative_y
+                )
+
+                self.has_reached_waypoint = True
+            else:
+                # Calculate relative x and y distance required to reach waypoint
+                relative_x = self.waypoint.location_x - report.position.location_x
+                relative_y = self.waypoint.location_y - report.position.location_y
+
+                command = commands.Command.create_set_relative_destination_command(
+                    relative_x, relative_y
+                )
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============
 
         return command
+
+    def __squared_distance(
+        self, location1: location.Location, location2: location.Location
+    ) -> float:
+        """
+        Calculate the distance between two Location objects.
+        """
+
+        return ((location2.location_x - location1.location_x) ** 2) + (
+            (location2.location_y - location1.location_y) ** 2
+        )

modules/bootcamp/detect_landing_pad.py

@@ -19,7 +19,6 @@
 # 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 +97,37 @@ def run(self, image: np.ndarray) -> "tuple[list[bounding_box.BoundingBox], np.nd
         # * conf
         # * device
         # * verbose
-        predictions = ...
+        predictions = self.__model.predict(
+            source=image, conf=0.7, device=self.__DEVICE, verbose=False
+        )
 
         # 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 xyxy_box in boxes_cpu:
+            # Create BoundingBox object and append to list
+            success, box = bounding_box.BoundingBox.create(xyxy_box)
+
+            if not success:
+                continue
+
+            bounding_boxes.append(box)
 
-        return [], image_annotated
+        return bounding_boxes, image_annotated
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============

requirements.txt

@@ -17,7 +17,6 @@ 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
 
 # ============
 # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑