-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
* 2 windows for left and right hand * using mediapipe fr but only showing hand1/2 instead of left/right * better display, still only hand 1 or 2 * linting --------- Co-authored-by: Skaiste Motiejunaite <[email protected]>
- Loading branch information
1 parent
72f0ae0
commit 5af615e
Showing
2 changed files
with
170 additions
and
59 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,106 @@ | ||
| """Hand Gesture and Image display for Hand 1 and Hand 2, no distinction between left or right""" | ||
| import sys | ||
| import cv2 | ||
| import mediapipe as mp | ||
| import numpy as np | ||
| from mediapipe.tasks import python | ||
| from mediapipe.tasks.python import vision | ||
|
|
||
| # Define paths in a separate dictionary | ||
| icon_paths = { | ||
| 'Thumb_Up': '../../Datasets/HandIcons/thumbs_up.png', | ||
| 'Thumb_Down': '../../Datasets/HandIcons/thumbs_down.png', | ||
| 'Pointing_Up': '../../Datasets/HandIcons/point_up.png', | ||
| 'Victory': '../../Datasets/HandIcons/peace.png', | ||
| 'Closed_Fist': '../../Datasets/HandIcons/fist.png', | ||
| 'Open_Palm': '../../Datasets/HandIcons/wave.png', | ||
| 'ILoveYou': '../../Datasets/HandIcons/rock.png' | ||
| } | ||
|
|
||
| # Preload icons into a dictionary | ||
| gesture_icons = {} | ||
| for gesture_name, path in icon_paths.items(): | ||
| icon = cv2.imread(path, cv2.IMREAD_UNCHANGED) | ||
| if icon is None: | ||
| print(f"Warning: Unable to load image at {path}") # Debugging print | ||
| else: | ||
| gesture_icons[gesture_name] = icon | ||
|
|
||
| # Create a GestureRecognizer object. | ||
| base_options = python.BaseOptions(model_asset_path='gesture_recognizer.task') | ||
| options = vision.GestureRecognizerOptions(base_options=base_options, num_hands=2) | ||
|
|
||
| # Create the Gesture Recognizer instance | ||
| recognizer = vision.GestureRecognizer.create_from_options(options) | ||
|
|
||
| # Initialize video capture from webcam (0 for the default camera) | ||
| cap = cv2.VideoCapture(0) | ||
| if not cap.isOpened(): | ||
| print("Error: Could not open video device.") | ||
| sys.exit() # Use sys.exit() instead of exit() | ||
|
|
||
| blank_image = 255 * np.ones((500, 600, 3), dtype=np.uint8) # White blank image | ||
|
|
||
| def display_gesture_info(input_frame, gesture_data): | ||
| """Draw gesture info and load corresponding icons.""" | ||
| emoji_images = [blank_image.copy(), blank_image.copy()] # Initialize emoji for both hands | ||
|
|
||
| # Sort hands based on their x-coordinates (leftmost hand first) | ||
| sorted_hands = sorted(gesture_data, key=lambda x: x[1][0].x) | ||
|
|
||
| for index, (current_hand_gestures, current_hand_landmarks) in enumerate(sorted_hands): | ||
| # Get the top gesture for the hand | ||
| top_gesture = current_hand_gestures[0] | ||
| current_gesture_name = top_gesture.category_name # Get the recognized gesture name | ||
|
|
||
| # Prepare the text to display | ||
| gesture_text = f"Hand {index + 1}: {current_gesture_name} ({top_gesture.score:.2f})" | ||
| cv2.putText(input_frame, gesture_text, (10, 30 + index * 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2) | ||
|
|
||
| # Load the icon for the recognized gesture | ||
| if current_gesture_name in gesture_icons: | ||
| icon_image = gesture_icons[current_gesture_name] | ||
| emoji_images[index] = icon_image # Load the icon for Hand 1 or Hand 2 | ||
|
|
||
| # Draw landmarks for each hand | ||
| for landmark in current_hand_landmarks: # Each landmark is a NormalizedLandmark | ||
| x = int(landmark.x * input_frame.shape[1]) | ||
| y = int(landmark.y * input_frame.shape[0]) | ||
| cv2.circle(input_frame, (x, y), 5, (0, 255, 0), -1) | ||
|
|
||
| return emoji_images | ||
|
|
||
| while cap.isOpened(): | ||
| ret, frame = cap.read() | ||
| if not ret: | ||
| print("Error: Frame not captured.") | ||
| continue | ||
|
|
||
| rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) | ||
|
|
||
| # Create a MediaPipe image from the RGB frame | ||
| mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=rgb_frame) | ||
|
|
||
| # Recognize gestures in the input frame | ||
| recognition_result = recognizer.recognize(mp_image) | ||
|
|
||
| # Process the result for both hands | ||
| gestures_and_landmarks = [] | ||
| if recognition_result.gestures: | ||
| for hand_gestures, hand_landmarks in zip(recognition_result.gestures, recognition_result.hand_landmarks): | ||
| gestures_and_landmarks.append((hand_gestures, hand_landmarks)) | ||
|
|
||
| # Update emoji images with the recognized gestures | ||
| hand_images = display_gesture_info(frame, gestures_and_landmarks) | ||
|
|
||
| # Show emojis for both hands in separate windows | ||
| cv2.imshow('Hand 1 Emoji', hand_images[0]) # Show Hand 1 emoji | ||
| cv2.imshow('Hand 2 Emoji', hand_images[1]) # Show Hand 2 emoji | ||
| cv2.imshow('Hand Recognition with Emoji', frame) # Show the original frame | ||
|
|
||
| if cv2.waitKey(1) & 0xFF == ord('q'): | ||
| break | ||
|
|
||
| # Release the video capture and close the window | ||
| cap.release() | ||
| cv2.destroyAllWindows() |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters