Arushi's pull request

modules/bootcamp/decision_simple_waypoint.py

@@ -8,15 +8,12 @@
 from .. import drone_report
 
 # Disable for bootcamp use
-# pylint: disable-next=unused-import
 from .. import drone_status
 from .. import location
 from ..private.decision import base_decision
 
 
 # Disable for bootcamp use
-# No enable
-# pylint: disable=duplicate-code,unused-argument
 
 
 class DecisionSimpleWaypoint(base_decision.BaseDecision):
@@ -39,6 +36,10 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
 
         # Add your own
 
+        self.has_sent_landing_command = False
+        self.min_bounds = -60
+        self.max_bounds = 60
+
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============
@@ -69,6 +70,28 @@ def run(
         # ============
 
         # Do something based on the report and the state of this class...
+        # ensuring drone is within bounds
+        if (
+            self.waypoint.location_x >= self.min_bounds
+            and self.waypoint.location_x <= self.max_bounds
+            and self.waypoint.location_y >= self.min_bounds
+            and self.waypoint.location_y <= self.max_bounds
+        ):
+            # when the drone is halted but not at the destination
+            if (
+                report.status == drone_status.DroneStatus.HALTED
+                and report.destination != self.waypoint
+            ):
+                command = commands.Command.create_set_relative_destination_command(
+                    self.waypoint.location_x, self.waypoint.location_y
+                )
+            # when the drone is at the destination and is halted
+            if (
+                report.status == drone_status.DroneStatus.HALTED
+                and report.destination == self.waypoint
+            ):
+                command = commands.Command.create_land_command()
+                self.has_sent_landing_command = True
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑

modules/bootcamp/decision_waypoint_landing_pads.py

@@ -8,15 +8,12 @@
 from .. import drone_report
 
 # Disable for bootcamp use
-# pylint: disable-next=unused-import
 from .. import drone_status
 from .. import location
 from ..private.decision import base_decision
 
 
 # Disable for bootcamp use
-# No enable
-# pylint: disable=duplicate-code,unused-argument
 
 
 class DecisionWaypointLandingPads(base_decision.BaseDecision):
@@ -38,11 +35,21 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
         # ============
 
         # Add your own
+        self.has_sent_landing_command = False
+        self.min_bounds = -60
+        self.max_bounds = 60
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============
 
+    def min_dist_squared(self, landing_pads: location.Location) -> float:
+        """returns distance squared"""
+        dist = (self.waypoint.location_x - landing_pads.location_x) ** 2 + (
+            self.waypoint.location_y - landing_pads.location_y
+        ) ** 2
+        return dist
+
     def run(
         self, report: drone_report.DroneReport, landing_pad_locations: "list[location.Location]"
     ) -> commands.Command:
@@ -69,6 +76,43 @@ def run(
         # ============
 
         # Do something based on the report and the state of this class...
+        if (
+            self.waypoint.location_x >= self.min_bounds
+            and self.waypoint.location_x <= self.max_bounds
+            and self.waypoint.location_y >= self.min_bounds
+            and self.waypoint.location_y <= self.max_bounds
+        ):
+            proximity = (self.waypoint.location_x - report.position.location_x) ** 2 + (
+                self.waypoint.location_y - report.position.location_y
+            ) ** 2
+            new_pad = location.Location(0, 0)
+            # checking if the drone is halted
+            if report.status == drone_status.DroneStatus.HALTED:
+
+                # when drone is at the nearest landing pad
+                if self.has_sent_landing_command:
+                    command = commands.Command.create_land_command()
+
+                # finding nearest landing pad and setting relative destination
+                elif not self.has_sent_landing_command and proximity < self.acceptance_radius**2:
+                    smallest_dist = float("inf")
+                    for landing_pads in landing_pad_locations:
+                        new_dist = self.min_dist_squared(landing_pads)
+                        if new_dist < smallest_dist:
+                            smallest_dist = new_dist
+                            new_pad = landing_pads
+
+                    command = commands.Command.create_set_relative_destination_command(
+                        new_pad.location_x - self.waypoint.location_x,
+                        new_pad.location_y - self.waypoint.location_y,
+                    )
+                    self.has_sent_landing_command = True
+
+                # setting relative destination to designated waypoint
+                elif proximity > self.acceptance_radius and not self.has_sent_landing_command:
+                    command = commands.Command.create_set_relative_destination_command(
+                        self.waypoint.location_x, self.waypoint.location_y
+                    )
 
         # ============
         # ↑ 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 +96,42 @@ def run(self, image: np.ndarray) -> "tuple[list[bounding_box.BoundingBox], np.nd
         # * conf
         # * device
         # * verbose
-        predictions = ...
+        # model = ultralytics.YOLO("yolov8n.pt")
+        predictions = self.__model.predict(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()
 
         # 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 = ...
+        # result, box = ...
+        # result=0
+
+        for i in range(0, np.shape(boxes_cpu)[0]):
+
+            (result, box) = bounding_box.BoundingBox.create(boxes_cpu[i])
+
+            if result:
+                bounding_boxes.append(box)
+            else:
+                return [], image_annotated
 
-        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 = 4  # seconds
 
 # OpenCV ignores your display settings,
 # so if the window is too small or too large,