Himank Bootcamp PR

.gitignore

@@ -9,3 +9,6 @@ venv/
 
 # Logging
 *log*
+
+# pyenv
+.python-version

modules/bootcamp/decision_simple_waypoint.py

@@ -37,12 +37,43 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float):
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Add your own
+        self.action_dict = dict(zip(("MOVE", "HALT", "LAND"), range(3,6)))
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============
 
+    def distance_between_waypoint(self, given_location:location.Location) -> bool:
+        """
+        Returns the distance between the given location and waypoint.
+        """
+        given_loc_from_waypoint_location_x = self.waypoint.location_x - given_location.location_x
+        given_loc_from_waypoint_location_y = self.waypoint.location_y - given_location.location_y
+        return (given_loc_from_waypoint_location_x, given_loc_from_waypoint_location_y)
+
+    def check_if_near_waypoint(self, given_location:location.Location) -> bool:
+        """
+        Checks if the given location is on the waypoint by an acceptance radius.
+        """
+        absolute_acceptance_radius = abs(self.acceptance_radius)
+        difference_location_x, difference_location_y = self.distance_between_waypoint(given_location)
+        if abs(difference_location_x) < absolute_acceptance_radius and abs(difference_location_y) < absolute_acceptance_radius:
+            return True
+        return False
+
+    def next_relative_coordinates_to_waypoint(self, given_location:location.Location) -> "tuple[float]":
+        """
+        Returns the relative x and y coordinates for drone to be sent to.
+        """
+        relative_x, relative_y = self.distance_between_waypoint(given_location)
+        divider = 1
+        if abs(relative_x) > abs(relative_y):
+            return (relative_x/divider, relative_y)
+        elif abs(relative_x) < abs(relative_y):
+            return (relative_x, relative_y/divider)
+        else:
+            return (relative_x/divider, relative_y/divider)
+
     def run(self,
             report: drone_report.DroneReport,
             landing_pad_locations: "list[location.Location]") -> commands.Command:
@@ -68,10 +99,32 @@ def run(self,
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Do something based on the report and the state of this class...
+        action = None
+        report_status = report.status
+        report_position = report.position
+
+        if report_status == drone_status.DroneStatus.LANDED:
+            action = None
+        elif report_status == drone_status.DroneStatus.HALTED:
+            if self.check_if_near_waypoint(report_position):
+                action = self.action_dict["LAND"]
+            else:
+                action = self.action_dict["MOVE"]
+        """ elif report_status == drone_status.DroneStatus.MOVING:
+            action = self.action_dict["HALT"] """
+
+        if action is None:
+            pass
+        elif action == self.action_dict["MOVE"]:
+            relative_x, relative_y = self.next_relative_coordinates_to_waypoint(report_position)
+            command = commands.Command.create_set_relative_destination_command(relative_x, relative_y)
+        elif action == self.action_dict["HALT"]:
+            command = commands.Command.create_halt_command()
+        elif action == self.action_dict["LAND"]:
+            command = commands.Command.create_land_command()
 
         # Remove this when done
-        raise NotImplementedError
+        # raise NotImplementedError
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑

modules/bootcamp/decision_waypoint_landing_pads.py

@@ -37,12 +37,67 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float):
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Add your own
+        self.action_dict = dict(zip(("MOVE", "HALT", "LAND"), range(3,6)))
+        self.origin = location.Location(0,0)
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============
 
+    def relative_coordinates_of_target(self, target_location:location.Location, given_location:location.Location) -> bool:
+        """
+        Returns the relative coordinates of target w.r.t given location.
+        """
+        relative_location_x = target_location.location_x - given_location.location_x
+        relative_location_y = target_location.location_y - given_location.location_y
+        return (relative_location_x, relative_location_y)
+
+    def check_if_near_target(self, target_location:location.Location, given_location:location.Location) -> bool:
+        """
+        Checks if the given location is near the target by an acceptance radius.
+        """
+        absolute_acceptance_radius = abs(self.acceptance_radius)
+        difference_location_x, difference_location_y = self.relative_coordinates_of_target(target_location, given_location)
+        if abs(difference_location_x) < absolute_acceptance_radius and abs(difference_location_y) < absolute_acceptance_radius:
+            return True
+        return False
+
+    def next_relative_coordinates_to_target(self,
+                                            target_location:location.Location,
+                                            given_location:location.Location) -> "tuple[float]":
+        """
+        Returns the relative x and y coordinates for drone to be sent to.
+        """
+        relative_x, relative_y = self.relative_coordinates_of_target(target_location, given_location)
+        divider = 1
+        if abs(relative_x) > abs(relative_y):
+            return (relative_x/divider, relative_y)
+        elif abs(relative_x) < abs(relative_y):
+            return (relative_x, relative_y/divider)
+        else:
+            return (relative_x/divider, relative_y/divider)
+
+    def closest_landing_pad(self,
+                            given_location:location.Location,
+                            landing_pad_locations: "list[location.Location]") -> location.Location:
+        """
+        Finds out the closest landing pad from the given location by checking out their distances.
+        """
+        def shortest_distance(target_location:location.Location, given_location:location.Location) -> float:
+            """
+            Finds out the shortest distance between two given locations.
+            """
+            x_1, y_1 = given_location.location_x, given_location.location_y
+            x_2, y_2 = target_location.location_x, target_location.location_y
+            x_square = (x_2 - x_1) ** 2
+            y_square = (y_2 - y_1) ** 2
+            return (x_square + y_square) ** 0.5
+        landing_pad_distances = list(map(lambda loc: shortest_distance(loc, given_location), landing_pad_locations))
+        landing_pad_hashmap = dict(zip(landing_pad_locations, landing_pad_distances))
+        landing_pad_hashmap = tuple(sorted(list(landing_pad_hashmap.items()), key=lambda i: i[1]))
+        return landing_pad_hashmap[0][0]
+
+
     def run(self,
             report: drone_report.DroneReport,
             landing_pad_locations: "list[location.Location]") -> commands.Command:
@@ -68,10 +123,53 @@ def run(self,
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Do something based on the report and the state of this class...
+        def shortest_distance(target_location:location.Location, given_location:location.Location) -> float:
+            """
+            Finds out the shortest distance between two given locations.
+            """
+            x_1, y_1 = given_location.location_x, given_location.location_y
+            x_2, y_2 = target_location.location_x, target_location.location_y
+            x_square = (x_2 - x_1) ** 2
+            y_square = (y_2 - y_1) ** 2
+            return (x_square + y_square) ** 0.5
+
+        action = None
+        report_status = report.status
+        report_position = report.position
+        target = self.waypoint
+
+        if report_status in (drone_status.DroneStatus.LANDED, drone_status.DroneStatus.MOVING):
+            pass
+        elif report_status == drone_status.DroneStatus.HALTED:
+            landing_pad = self.closest_landing_pad(self.waypoint, landing_pad_locations)
+            action = self.action_dict["MOVE"]
+            if self.check_if_near_target(self.waypoint, report_position):
+                target = landing_pad
+            if (self.check_if_near_target(landing_pad, report_position)
+                and (shortest_distance(self.waypoint, report_position) - shortest_distance(self.waypoint, landing_pad) < 0.1)
+                and (
+                    (self.check_if_near_target(landing_pad, self.origin) and self.check_if_near_target(self.waypoint, self.origin))
+                    or (not self.check_if_near_target(report_position, self.origin))
+                )):
+                """ 
+                self.check_if_near_target(landing_pad, self.origin) - if nearest landing pad is origin
+                self.check_if_near_target(self.waypoint, self.origin) - if waypoint is origin
+                self.check_if_near_target(report_position, self.origin) - if current position is origin
+                """
+                action = self.action_dict["LAND"]
+
+        if action is None:
+            pass
+        elif action == self.action_dict["MOVE"]:
+            relative_x, relative_y = self.next_relative_coordinates_to_target(target, report_position)
+            command = commands.Command.create_set_relative_destination_command(relative_x, relative_y)
+        elif action == self.action_dict["HALT"]:
+            command = commands.Command.create_halt_command()
+        elif action == self.action_dict["LAND"]:
+            command = commands.Command.create_land_command()
 
         # Remove this when done
-        raise NotImplementedError
+        # raise NotImplementedError
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑

modules/bootcamp/detect_landing_pad.py

@@ -86,32 +86,38 @@ 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.__getitem__(0)
 
         # Plot the annotated image from the Result object
         # Include the confidence value
-        image_annotated = ...
+        image_annotated = prediction.plot(pil=True, 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 = prediction.boxes.cpu().xyxy.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, ...):
+        for i in range(0, boxes_cpu.shape[0]):
             # Create BoundingBox object and append to list
-            # result, box = ...
+            result, box = bounding_box.BoundingBox.create(boxes_cpu[i])
+            if result:
+                bounding_boxes.append(box)
 
         # Remove this when done
-        raise NotImplementedError
+        # raise NotImplementedError
+        return (bounding_boxes, image_annotated)
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑

modules/bootcamp/tests/run_decision_example.py

@@ -41,7 +41,7 @@
 # OpenCV ignores your display settings,
 # so if the window is too small or too large,
 # change this value (between 0.0 and 1.0)
-DISPLAY_SCALE = 0.8
+DISPLAY_SCALE = 0.7
 
 # Seed for randomly generating the waypoint and landing pad
 # Change to a constant for reproducibility (e.g. debugging)

modules/bootcamp/tests/run_decision_simple_waypoint.py

@@ -34,12 +34,12 @@
 # You can probably divide it by 10 or so since ML inference isn't running
 # Increase the step size if your computer is lagging
 # Larger step size is smaller FPS
-TIME_STEP_SIZE = 0.01  # seconds
+TIME_STEP_SIZE = 0.1  # seconds
 
 # OpenCV ignores your display settings,
 # so if the window is too small or too large,
 # change this value (between 0.0 and 1.0)
-DISPLAY_SCALE = 0.8
+DISPLAY_SCALE = 0.7
 
 # Seed for randomly generating the waypoint and landing pad
 # Change to a constant for reproducibility (e.g. debugging)

modules/bootcamp/tests/run_decision_waypoint_landing_pads.py

@@ -46,7 +46,7 @@
 # Seed for randomly generating the waypoint and landing pad
 # Change to a constant for reproducibility (e.g. debugging)
 # Change back to = time.time_ns() to test robustness
-SEED = time.time_ns()
+SEED = time.time_ns() # 1694668265382892400
 
 # ============
 # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑