Inital Commit

DataStreamModule.py

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+import cv2
+import numpy as np
+from IDataStreamModule import IDataStreamModule
+
+
+class DataStreamModule(IDataStreamModule):
+
+    # Method to find available cameras and return their IDs
+    def findCameras(self):
+        # List to store the IDs of the found cameras
+        cameras = []
+        # Iterating through all possible camera IDs
+        i = 0
+        while True:
+            cap = cv2.VideoCapture(i)
+            if not cap.isOpened():
+                # No further cameras found, break the loop
+                break
+            # Camera found, store ID in the list
+            cameras.append(i)
+            cap.release()
+            i += 1
+        # Return the IDs of the found cameras
+        return cameras
+
+    # Method to get the camera stream from a given camera
+    def get_camera_stream(self, camera_name):
+        cap = cv2.VideoCapture(camera_name)
+        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+        current_frame = 0
+        while cap.isOpened():
+            ret, frame = cap.read()
+            # Yield each frame as a numpy array
+            yield np.array(frame)
+            current_frame += 1
+            if current_frame == total_frames - 1:
+                # If the current frame is the second-to-last frame, reset to the beginning of the file
+                cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
+                current_frame = 0
+        cap.release()

HPEModule.py

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+import cv2
+import mediapipe as mp
+from DataStreamModule import DataStreamModule
+from IHPEModule import IHPEModule
+
+# initialize mediapipe drawing utilities and pose models
+mp_drawing = mp.solutions.drawing_utils
+mp_pose = mp.solutions.pose
+
+
+# This class implements Human Pose Estimation (HPE) using the mediapipe library
+class HPEModule(IHPEModule):
+
+    # This method starts HPE using a camera specified by its name
+    def startHPEwithCamera(self, camera_name):
+
+        # initialize data stream and camera object
+        data_stream = DataStreamModule()
+        cap = data_stream.get_camera_stream(camera_name)
+
+        # set the window name using the camera name
+        window_name = f"Pose Estimation on Camera {camera_name}"
+
+        # start pose detection
+        with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
+            while True:
+                # get the next frame from the camera
+                frame = next(cap)
+
+                # Recolor image to RGB
+                image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+                image.flags.writeable = False
+
+                # Make detection
+                results = pose.process(image)
+
+                # Recolor back to BGR
+                image.flags.writeable = True
+                image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+
+                # Extract landmarks
+                try:
+                    landmarks = results.pose_landmarks.landmark
+                    print(landmarks)
+                except:
+                    pass
+
+                # Render detections
+                mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,
+                                          mp_drawing.DrawingSpec(color=(245, 117, 66), thickness=2, circle_radius=2),
+                                          mp_drawing.DrawingSpec(color=(245, 66, 230), thickness=2, circle_radius=2)
+                                          )
+
+                cv2.imshow(window_name, image)
+                keyCode = cv2.waitKey(1)
+                if cv2.getWindowProperty(window_name, cv2.WND_PROP_VISIBLE) < 1:
+                    break
+
+            # destroy the window after exiting the loop
+            #cv2.destroyWindow(window_name)

IDataStreamModule.py

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+from abc import ABC, abstractmethod
+
+
+class IDataStreamModule(ABC):
+
+    # Method to find available cameras and return their IDs
+    @abstractmethod
+    def findCameras(self):
+        pass
+
+    # Method to get the camera stream from a given camera
+    @abstractmethod
+    def get_camera_stream(self, camera_name):
+        pass

IHPEModule.py

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+from abc import ABC, abstractmethod
+
+
+class IHPEModule(ABC):
+
+    # This method starts HPE using a camera specified by its name
+    @abstractmethod
+    def startHPEwithCamera(self, camera_name):
+        pass

PoseEstimationGUI.py

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+import tkinter as tk
+from DataStreamModule import DataStreamModule
+from HPEModule import HPEModule
+import threading
+
+
+class PoseEstimationGUI:
+
+    def __init__(self):
+        self.root = tk.Tk()
+        self.root.title("Pose Estimation GUI")
+
+        self.camera_options = []  # Initialize camera options list
+
+        # Create a drop-down menu with available cameras
+        self.camera_options = DataStreamModule().findCameras()
+        self.selected_camera = tk.StringVar()
+        self.selected_camera.set(self.camera_options[0])  # default value
+        camera_menu = tk.OptionMenu(self.root, self.selected_camera, *self.camera_options)
+        camera_menu.pack()
+
+        # Create a button to start pose estimation
+        self.start_button = tk.Button(self.root, text="Start Pose Estimation", command=self.start_pose_estimation)
+        self.start_button.pack()
+
+        self.root.mainloop()
+
+    def start_pose_estimation(self):
+        # Start pose estimation on the selected camera
+        # print(self.selected_camera.get())
+        pose_estimator = HPEModule()
+        camera = int(self.selected_camera.get())
+        pose_thread = threading.Thread(target=pose_estimator.startHPEwithCamera, args=(camera,))
+        pose_thread.start()
+
+
+if __name__ == '__main__':
+    PoseEstimationGUI()

main.py

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+from HPEModule import HPEModule
+
+if __name__ == '__main__':
+    pe = HPEModule()  # use camera 0
+    pe.startHPEwithCamera(0)