ultralytics 8.2.88 Update distance-calculation to pixels (ultraly…

…tics#15984)

Co-authored-by: UltralyticsAssistant <[email protected]>
Co-authored-by: Glenn Jocher <[email protected]>

docs/en/guides/distance-calculation.md

@@ -30,8 +30,7 @@ Measuring the gap between two objects is known as distance calculation within a
 ## Advantages of Distance Calculation?
 
 - **Localization Precision:** Enhances accurate spatial positioning in computer vision tasks.
-- **Size Estimation:** Allows estimation of physical sizes for better contextual understanding.
-- **Scene Understanding:** Contributes to a 3D understanding of the environment for improved decision-making.
+- **Size Estimation:** Allows estimation of object size for better contextual understanding.
 
 ???+ tip "Distance Calculation"
 
@@ -85,14 +84,13 @@ Measuring the gap between two objects is known as distance calculation within a
 
 ### Arguments `DistanceCalculation()`
 
-| `Name`             | `Type`  | `Default`       | Description                                               |
-| ------------------ | ------- | --------------- | --------------------------------------------------------- |
-| `names`            | `dict`  | `None`          | Dictionary of classes names.                              |
-| `pixels_per_meter` | `int`   | `10`            | Conversion factor from pixels to meters.                  |
-| `view_img`         | `bool`  | `False`         | Flag to indicate if the video stream should be displayed. |
-| `line_thickness`   | `int`   | `2`             | Thickness of the lines drawn on the image.                |
-| `line_color`       | `tuple` | `(255, 255, 0)` | Color of the lines drawn on the image (BGR format).       |
-| `centroid_color`   | `tuple` | `(255, 0, 255)` | Color of the centroids drawn (BGR format).                |
+| `Name`           | `Type`  | `Default`       | Description                                               |
+| ---------------- | ------- | --------------- | --------------------------------------------------------- |
+| `names`          | `dict`  | `None`          | Dictionary of classes names.                              |
+| `view_img`       | `bool`  | `False`         | Flag to indicate if the video stream should be displayed. |
+| `line_thickness` | `int`   | `2`             | Thickness of the lines drawn on the image.                |
+| `line_color`     | `tuple` | `(255, 255, 0)` | Color of the lines drawn on the image (BGR format).       |
+| `centroid_color` | `tuple` | `(255, 0, 255)` | Color of the centroids drawn (BGR format).                |
 
 ### Arguments `model.track`
 
@@ -133,7 +131,6 @@ To delete points drawn during distance calculation with Ultralytics YOLOv8, you
 The key arguments for initializing the `DistanceCalculation` class in Ultralytics YOLOv8 include:
 
 - `names`: Dictionary mapping class indices to class names.
-- `pixels_per_meter`: Conversion factor from pixels to meters.
 - `view_img`: Flag to indicate if the video stream should be displayed.
 - `line_thickness`: Thickness of the lines drawn on the image.
 - `line_color`: Color of the lines drawn on the image (BGR format).

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.2.87"
+__version__ = "8.2.88"
 
 import os
 

ultralytics/solutions/distance_calculation.py

@@ -14,18 +14,16 @@ class DistanceCalculation:
     def __init__(
         self,
         names,
-        pixels_per_meter=10,
         view_img=False,
         line_thickness=2,
-        line_color=(255, 255, 0),
-        centroid_color=(255, 0, 255),
+        line_color=(255, 0, 255),
+        centroid_color=(104, 31, 17),
     ):
         """
         Initializes the DistanceCalculation class with the given parameters.
 
         Args:
             names (dict): Dictionary of classes names.
-            pixels_per_meter (int, optional): Conversion factor from pixels to meters. Defaults to 10.
             view_img (bool, optional): Flag to indicate if the video stream should be displayed. Defaults to False.
             line_thickness (int, optional): Thickness of the lines drawn on the image. Defaults to 2.
             line_color (tuple, optional): Color of the lines drawn on the image (BGR format). Defaults to (255, 255, 0).
@@ -39,22 +37,21 @@ def __init__(
         self.centroid_color = centroid_color
 
         # Prediction & tracking information
-        self.clss = None
         self.names = names
         self.boxes = None
         self.line_thickness = line_thickness
         self.trk_ids = None
 
         # Distance calculation information
         self.centroids = []
-        self.pixel_per_meter = pixels_per_meter
 
         # Mouse event information
         self.left_mouse_count = 0
         self.selected_boxes = {}
 
         # Check if environment supports imshow
         self.env_check = check_imshow(warn=True)
+        self.window_name = "Ultralytics Solutions"
 
     def mouse_event_for_distance(self, event, x, y, flags, param):
         """
@@ -78,46 +75,6 @@ def mouse_event_for_distance(self, event, x, y, flags, param):
             self.selected_boxes = {}
             self.left_mouse_count = 0
 
-    def extract_tracks(self, tracks):
-        """
-        Extracts tracking results from the provided data.
-
-        Args:
-            tracks (list): List of tracks obtained from the object tracking process.
-        """
-        self.boxes = tracks[0].boxes.xyxy.cpu()
-        self.clss = tracks[0].boxes.cls.cpu().tolist()
-        self.trk_ids = tracks[0].boxes.id.int().cpu().tolist()
-
-    @staticmethod
-    def calculate_centroid(box):
-        """
-        Calculates the centroid of a bounding box.
-
-        Args:
-            box (list): Bounding box coordinates [x1, y1, x2, y2].
-
-        Returns:
-            (tuple): Centroid coordinates (x, y).
-        """
-        return int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2)
-
-    def calculate_distance(self, centroid1, centroid2):
-        """
-        Calculates the distance between two centroids.
-
-        Args:
-            centroid1 (tuple): Coordinates of the first centroid (x, y).
-            centroid2 (tuple): Coordinates of the second centroid (x, y).
-
-        Returns:
-            (tuple): Distance in meters and millimeters.
-        """
-        pixel_distance = math.sqrt((centroid1[0] - centroid2[0]) ** 2 + (centroid1[1] - centroid2[1]) ** 2)
-        distance_m = pixel_distance / self.pixel_per_meter
-        distance_mm = distance_m * 1000
-        return distance_m, distance_mm
-
     def start_process(self, im0, tracks):
         """
         Processes the video frame and calculates the distance between two bounding boxes.
@@ -135,10 +92,13 @@ def start_process(self, im0, tracks):
                 self.display_frames()
             return im0
 
-        self.extract_tracks(tracks)
+        self.boxes = tracks[0].boxes.xyxy.cpu()
+        clss = tracks[0].boxes.cls.cpu().tolist()
+        self.trk_ids = tracks[0].boxes.id.int().cpu().tolist()
+
         self.annotator = Annotator(self.im0, line_width=self.line_thickness)
 
-        for box, cls, track_id in zip(self.boxes, self.clss, self.trk_ids):
+        for box, cls, track_id in zip(self.boxes, clss, self.trk_ids):
             self.annotator.box_label(box, color=colors(int(cls), True), label=self.names[int(cls)])
 
             if len(self.selected_boxes) == 2:
@@ -147,12 +107,15 @@ def start_process(self, im0, tracks):
                         self.selected_boxes[track_id] = box
 
         if len(self.selected_boxes) == 2:
-            self.centroids = [self.calculate_centroid(self.selected_boxes[trk_id]) for trk_id in self.selected_boxes]
-
-            distance_m, distance_mm = self.calculate_distance(self.centroids[0], self.centroids[1])
-            self.annotator.plot_distance_and_line(
-                distance_m, distance_mm, self.centroids, self.line_color, self.centroid_color
+            # Store user selected boxes in centroids list
+            self.centroids.extend(
+                [[int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2)] for box in self.selected_boxes.values()]
+            )
+            # Calculate pixels distance
+            pixels_distance = math.sqrt(
+                (self.centroids[0][0] - self.centroids[1][0]) ** 2 + (self.centroids[0][1] - self.centroids[1][1]) ** 2
             )
+            self.annotator.plot_distance_and_line(pixels_distance, self.centroids, self.line_color, self.centroid_color)
 
         self.centroids = []
 
@@ -163,9 +126,9 @@ def start_process(self, im0, tracks):
 
     def display_frames(self):
         """Displays the current frame with annotations."""
-        cv2.namedWindow("Ultralytics Distance Estimation")
-        cv2.setMouseCallback("Ultralytics Distance Estimation", self.mouse_event_for_distance)
-        cv2.imshow("Ultralytics Distance Estimation", self.im0)
+        cv2.namedWindow(self.window_name)
+        cv2.setMouseCallback(self.window_name, self.mouse_event_for_distance)
+        cv2.imshow(self.window_name, self.im0)
 
         if cv2.waitKey(1) & 0xFF == ord("q"):
             return

ultralytics/utils/plotting.py

@@ -756,39 +756,35 @@ def seg_bbox(self, mask, mask_color=(255, 0, 255), label=None, txt_color=(255, 2
                 self.im, label, (int(mask[0][0]) - text_size[0] // 2, int(mask[0][1])), 0, self.sf, txt_color, self.tf
             )
 
-    def plot_distance_and_line(self, distance_m, distance_mm, centroids, line_color, centroid_color):
+    def plot_distance_and_line(self, pixels_distance, centroids, line_color, centroid_color):
         """
         Plot the distance and line on frame.
 
         Args:
-            distance_m (float): Distance between two bbox centroids in meters.
-            distance_mm (float): Distance between two bbox centroids in millimeters.
+            pixels_distance (float): Pixels distance between two bbox centroids.
             centroids (list): Bounding box centroids data.
             line_color (RGB): Distance line color.
             centroid_color (RGB): Bounding box centroid color.
         """
-        (text_width_m, text_height_m), _ = cv2.getTextSize(f"Distance M: {distance_m:.2f}m", 0, self.sf, self.tf)
-        cv2.rectangle(self.im, (15, 25), (15 + text_width_m + 10, 25 + text_height_m + 20), line_color, -1)
-        cv2.putText(
-            self.im,
-            f"Distance M: {distance_m:.2f}m",
-            (20, 50),
-            0,
-            self.sf,
-            centroid_color,
-            self.tf,
-            cv2.LINE_AA,
+        # Get the text size
+        (text_width_m, text_height_m), _ = cv2.getTextSize(
+            f"Pixels Distance: {pixels_distance:.2f}", 0, self.sf, self.tf
         )
 
-        (text_width_mm, text_height_mm), _ = cv2.getTextSize(f"Distance MM: {distance_mm:.2f}mm", 0, self.sf, self.tf)
-        cv2.rectangle(self.im, (15, 75), (15 + text_width_mm + 10, 75 + text_height_mm + 20), line_color, -1)
+        # Define corners with 10-pixel margin and draw rectangle
+        top_left = (15, 25)
+        bottom_right = (15 + text_width_m + 20, 25 + text_height_m + 20)
+        cv2.rectangle(self.im, top_left, bottom_right, centroid_color, -1)
+
+        # Calculate the position for the text with a 10-pixel margin and draw text
+        text_position = (top_left[0] + 10, top_left[1] + text_height_m + 10)
         cv2.putText(
             self.im,
-            f"Distance MM: {distance_mm:.2f}mm",
-            (20, 100),
+            f"Pixels Distance: {pixels_distance:.2f}",
+            text_position,
             0,
             self.sf,
-            centroid_color,
+            (255, 255, 255),
             self.tf,
             cv2.LINE_AA,
         )