Added original air_draw file

Air_Draw_RGB.py

@@ -1,161 +0,0 @@
-import cv2
-import numpy as np
-from PIL import Image
-import mediapipe as mp
-import time
-import gradio as gr
-
-DOMINANT_HAND = "Right"
-
-width, height = 1280, 720
-width_, height_, = 256, 144
-
-
-def find_hands(brain, img):
-    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) # opencv image is in BGR form but mp is trained with RGB
-    results = brain.process(img_rgb) # process finds the hands and outputs classification and 21 landmarks for each hand
-    all_hands = [] # initializing array to hold the dictionary for the hands
-    h, w, _ = img.shape # get height and width of image for scaling
-    if results.multi_hand_landmarks:
-        for hand_type, hand_lms in zip(results.multi_handedness, results.multi_hand_landmarks): # elegant solution for mp list object traversal
-            hand = {} # initializing dict for each hand
-            lm_list = [] # landmarks array for all 21 point of the hand
-            for lm in hand_lms.landmark:
-                px, py, pz = int(lm.x * w), int(lm.y * h), int(lm.z * w) # scaling landmark points to image size for frame coordinates
-                lm_list.append([px, py, pz])
-
-            hand["lm_list"] = lm_list # add "lm_list" key for all landmark points of the hand
-            hand["type"] = hand_type.classification[0].label # adds the label (left/right) for the hand
-            all_hands.append(hand) # appends the dict
-    return all_hands
-
-
-def is_drawing(index, thumb): # proximity function with arbitrary threshold
-    npindex = np.array((index[0], index[1]))
-    npthumb = np.array((thumb[0], thumb[1]))
-    if np.linalg.norm(npindex - npthumb) < 30:
-        return True
-    else:
-        return False
-
-
-def save(landmarks): # brute force finger orientation checking
-    if landmarks[8][1] < landmarks[6][1]:
-        if landmarks[12][1] < landmarks[10][1]:
-            if landmarks[16][1] < landmarks[14][1]:
-                if landmarks[20][1] < landmarks[18][1]:
-                    return True
-    else:
-        return False
-
-def clear(landmarks): # brute force finger orientation checking
-    if landmarks[4][1] < landmarks[3][1] < landmarks[2][1] < landmarks[8][1]:
-        return True
-    else:
-        return False
-
-drawing_flag = False
-sleepy_time = time.time()
-
-if __name__ == '__main__':
-    cam = cv2.VideoCapture(0)
-    cam.set(3, width)
-    cam.set(4, height)
-
-    detector = mp.solutions.hands.Hands(min_detection_confidence=0.8) # initialize mp model
-    # paper = np.zeros((width, height, 4), np.uint8)
-    paper = np.zeros((height, width, 3), dtype=np.uint8) # create blank page
-    paper.fill(255)
-
-    past_holder = () # coordinates holder
-    palette = cv2.imread('palette.jpg')
-
-    output_frames = []
-    page_num = 0
-    # runny = 1
-    color = (0, 0, 0)
-    while True:
-        # runny -= 1
-        x, rgb_image = cam.read()
-        rgb_image_f = cv2.flip(np.asanyarray(rgb_image), 1)
-
-        hands = find_hands(detector, rgb_image_f)
-
-        try:
-            if hands:
-                hand1 = hands[0] if hands[0]["type"] == DOMINANT_HAND else hands[1]
-                lm_list1 = hand1["lm_list"]  # List of 21 Landmarks
-                handedness = hand1["type"]
-
-                if handedness == DOMINANT_HAND:
-                    idx_coords = lm_list1[8][0], lm_list1[8][1]  # 0 is width (bigger)
-                    # print(idx_coords)
-                    cv2.circle(rgb_image_f, idx_coords, 5, color, cv2.FILLED)
-
-                    if idx_coords[1] < 72: # brute force but should be extremely marginally faster lol
-                        if idx_coords[0] < 142:  # red
-                            color = (0, 0, 255)
-                        if 142 < idx_coords[0] < 285:  # orange
-                            color = (0, 115, 255)
-                        if 285 < idx_coords[0] < 426:  # yellow
-                            color = (0, 229, 255)
-                        if 426 < idx_coords[0] < 569:  # green
-                            color = (0, 195, 88)
-                        if 569 < idx_coords[0] < 711:  # blue
-                            color = (195, 85, 0)
-                        if 711 < idx_coords[0] < 853:  # indigo
-                            color = (195, 0, 68)
-                        if 853 < idx_coords[0] < 996:  # violet
-                            color = (195, 0, 143)
-                        if 996 < idx_coords[0] < 1137:  # black
-                            color = (0, 0, 0)
-                        if 1137 < idx_coords[0]:  # white / eraser
-                            color = (255, 255, 255)
-
-                    if len(past_holder) and drawing_flag: # start drawing
-                        cv2.line(paper, past_holder, idx_coords, color, 5)
-                        cv2.line(rgb_image_f, past_holder, idx_coords, color, 5)
-                        # paper[idx_coords[0]][idx_coords[1]][0] = 255
-                        # paper[idx_coords[0]][idx_coords[1]][3] = 255
-                        cv2.circle(rgb_image_f, idx_coords, 5, color, cv2.FILLED)
-
-                    if save(lm_list1) and time.time() - sleepy_time > 3: # save page, 3 secs arbitrary, just to not iterate every loop iteration
-                        paper[0:height_, w - width_: w] = 255
-                        paper = cv2.cvtColor(paper, cv2.COLOR_BGR2RGB)
-                        im = Image.fromarray(paper)
-                        im.save("paper%s.png" % page_num)
-                        print("saved")
-                        sleepy_time = time.time()
-                        paper = cv2.cvtColor(paper, cv2.COLOR_RGB2BGR)
-                        page_num += 1
-
-                    if clear(lm_list1) and time.time() - sleepy_time > 3: # clear page
-                        paper = np.zeros((height, width, 3), dtype=np.uint8)
-                        paper.fill(255)
-                        print("page cleared")
-                        sleepy_time = time.time()
-
-                    past_holder = idx_coords
-
-            if is_drawing(idx_coords, lm_list1[4]):  # 4 is thumb for intuitive "hold pen" to draw
-                drawing_flag = True
-            else:
-                drawing_flag = False
-
-        except:
-            pass
-
-        finally:
-            rgb_image_f[0:72, ] = palette
-            presenter = cv2.resize(rgb_image_f, (width_, height_))
-            h, w, _ = rgb_image_f.shape
-            paper[0:height_, w - width_: w] = presenter
-            cv2.imshow("Image", rgb_image_f)
-            cv2.imshow("paper", paper)
-            key = cv2.waitKey(1)
-            if key & 0xFF == ord('q') or key == 27:  # Press esc or 'q' to close the image window
-                break
-            output_frames.append(paper)
-
-
-    print("output: ", type(output_frames))