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| from numpy.core.records import record | |
| import streamlit as st | |
| st.set_page_config( | |
| page_title="Game Keys", | |
| page_icon="🎮", | |
| layout="wide", | |
| initial_sidebar_state="expanded" | |
| ) | |
| import pandas as pd | |
| import numpy as np | |
| import cv2 | |
| import mediapipe as mp | |
| import time | |
| from PIL import Image | |
| import tempfile | |
| DEMO_IMAGE = 'demo.jpg' | |
| DEMO_VIDEO = 'test3.mp4' | |
| prevTime=0 | |
| currTime=0 | |
| tipIds= [4,8,12,16,20] | |
| st.title('Game Keys with Hand Tracking Web-App') | |
| import webbrowser | |
| url = 'https://github.com/shashankanand13monu/Game-Automation' | |
| # if st.button('Code'): | |
| # webbrowser.open_new_tab(url) | |
| # st.set_page_config( | |
| # page_title="Ex-stream-ly Cool App", | |
| # page_icon="🧊", | |
| # layout="wide", | |
| # initial_sidebar_state="expanded" | |
| # ) | |
| mp_drawing = mp.solutions.drawing_utils | |
| mp_draw= mp.solutions.drawing_utils | |
| mp_face_mesh = mp.solutions.face_mesh | |
| mp_draw= mp.solutions.drawing_utils | |
| mp_hand= mp.solutions.hands | |
| mp_hands = mp.solutions.hands | |
| # mp_drawing = mp.solutions.drawing_utils | |
| mp_drawing_styles = mp.solutions.drawing_styles | |
| # mp_hands = mp.solutions.hands | |
| # mp_hand= mp.solutions.hands | |
| # mp_drawing = mp.solutions.drawing_utils | |
| # mp_drawing_styles = mp.solutions.drawing_styles | |
| # mp_hands = mp.solutions.hands | |
| t = st.empty() | |
| def draw(str): | |
| # t.subheader(str) | |
| # original_title = 'f<p style="font-family:Arial Black; color:red; font-size: 30px;">{str}</p>' | |
| # st.markdown('f<p style="font-family:Arial Black; color:red; font-size: 30px;">{str}</p>', unsafe_allow_html=True) | |
| t.markdown(f'<p style="font-family:Arial Black;color:#FF0686;font-size:28px;;">{str}</p>', unsafe_allow_html=True) | |
| # variable_output = str | |
| # font_size = 30 | |
| # html_str = f""" | |
| # <style> | |
| # p.a {{ | |
| # font: bold {font_size}px Courier; | |
| # }} | |
| # </style> | |
| # <p class="a">{variable_output}</p> | |
| # """ | |
| # st.markdown(html_str, unsafe_allow_html=True) | |
| st.markdown( | |
| """ | |
| <style> | |
| [data-testid="stSidebar"][aria-expanded="true"] > div:first-child{ | |
| width: 350px | |
| } | |
| [data-testid="stSidebar"][aria-expanded="false"] > div:first-child{ | |
| width: 350px | |
| margin-left: -350px | |
| </style> | |
| """,unsafe_allow_html=True,) | |
| if st.sidebar.button('Code'): | |
| webbrowser.open_new_tab(url) | |
| st.sidebar.title('Menu') | |
| st.sidebar.subheader('Settings') | |
| def image_resize(image, width=None, height=None, inter =cv2.INTER_AREA): | |
| dim = None | |
| (h ,w) = image.shape[:2] | |
| if width is None and height is None: | |
| return image | |
| if width is None: | |
| r= width/float(w) | |
| dim = (int(w*r), height) | |
| else: | |
| r = width/float(w) | |
| dim = (width, int(h*r)) | |
| #resize the image | |
| resized =cv2.resize(image, dim ,interpolation=inter) | |
| return resized | |
| app_mode= st.sidebar.selectbox('Choose the App Mode', | |
| ['About App','Run on Image','Run On Video']) | |
| # st.sidebar.markdown('---') | |
| # st.sidebar.button('Code') | |
| # st.sibutton('Code') | |
| # if st.sidebar.button('Code'): | |
| # webbrowser.open_new_tab(url) | |
| if app_mode== 'About App': | |
| st.markdown('App Made using **Mediapipe** & **Open CV**') | |
| st.markdown( | |
| """ | |
| <style> | |
| [data-testid="stSidebar"][aria-expanded="true"] > div:first-child{ | |
| width: 350px | |
| } | |
| [data-testid="stSidebar"][aria-expanded="false"] > div:first-child{ | |
| width: 350px | |
| margin-left: -350px | |
| </style> | |
| """,unsafe_allow_html=True,) | |
| st.markdown(''' | |
| # Tutorial \n | |
| ''' | |
| ) | |
| original_title = '<pre style="font-family:Aku & Kamu; color:#FD0177; font-size: 25px;font-weight:Bold">🕹️ W- 5 Fingers 🕹️ A- 2 or 3 Fingers</pre>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| original_title = '<pre style="font-family:Aku & Kamu; color:#FD0177; font-size: 25px;font-weight:Bold;">🕹️ S- Fist 🕹️ D- 4 Fingers</pre>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| # st.subheader('''W - 5 Fingers''') | |
| # st.subheader('S - Fist\n A - 2 or 3 Fingers\n D - 4 Fingers') | |
| st.image('wsad.jpg',width=200) | |
| original_title = '<pre style="font-family:Aku & Kamu; color:#FD0101 ; font-size: 28px;font-weight:Bold">*NOTE</pre>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| original_title= '''<pre style="font-family:Aku & Kamu; color:#270F40; font-size: 24px;"> | |
| Video Option will Experience Lag in Browsers. | |
| If It's <strong>Lagging</strong> just <strong>Reload</strong> & Choose your option <strong>ASAP</strong> | |
| eg: <strong>Choosing Max Hands</strong> or <strong>Using Webcam.</strong> | |
| Webcam Will Take about <strong>20 Seconds</strong> to Load</pre>''' | |
| # st.markdown('''Video Option will Experience **Lag** in **Browsers**. If It's **Lagging** just **Reload** & Choose your option ASAP eg: **Choosing Max Hands** or **Using Webcam**. Webcam Will Take about **20 Seconds** to Load ''') | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| elif app_mode == 'Run on Image': | |
| drawing_spec = mp_drawing.DrawingSpec(thickness=2, circle_radius=1) | |
| st.sidebar.markdown ('---------' ) | |
| st.markdown( | |
| """ | |
| <style> | |
| [data-testid="stSidebar"][aria-expanded="true"] > div:first-child{ | |
| width: 350px | |
| } | |
| [data-testid="stSidebar"][aria-expanded="false"] > div:first-child{ | |
| width: 350px | |
| margin-left: -350px | |
| </style> | |
| """,unsafe_allow_html=True,) | |
| # st.markdown("**Detected Hands**") | |
| st.header("** Detected Hands **") | |
| kpi1_text = st.markdown("0") | |
| max_hands= st.sidebar.number_input('Maximum Number of Hands',value=2,min_value=1,max_value=4) | |
| # st.sidebar('---') | |
| detection_confidence= st.sidebar.slider('Detection Confidence',min_value=0.0,max_value=1.0,value=0.5) | |
| st.sidebar.markdown('---') | |
| IMAGE_FILE=[] | |
| count=0 | |
| img_file_buffer = st.sidebar.file_uploader("Upload an Image", type=["jpg","jpeg", "png"]) | |
| if img_file_buffer is not None: | |
| file_bytes = np.asarray(bytearray(img_file_buffer.read()), dtype=np.uint8) | |
| opencv_image = cv2.imdecode(file_bytes, 1) | |
| image = opencv_image.copy() | |
| # image = np.array(Image.open(img_file_buffer)) | |
| else: | |
| demo_image= DEMO_IMAGE | |
| # file_bytes = np.asarray(bytearray(demo_image.read()), dtype=np.uint8) | |
| # opencv_image = cv2.imdecode(file_bytes, 1) | |
| # image = opencv_image.copy() | |
| # image= np.array(Image.open(demo_image)) | |
| image = 'demo.jpg' | |
| cap = cv2.imread('demo.jpg', cv2.IMREAD_UNCHANGED) | |
| image = cap.copy() | |
| # st.sidebar.text('Input Image') | |
| st.sidebar.subheader('Input Image') | |
| image = cv2.cvtColor(image,cv2.COLOR_BGR2RGB) | |
| st.sidebar.image(image) | |
| # st.sidebar.markdown('---') | |
| # st.sidebar.text('Demo Image') | |
| st.sidebar.subheader('Demo Images') | |
| # st.sidebar.image('WIN_20211106_14_34_25_Pro.jpg') | |
| st.sidebar.image('dddemo.jpg') | |
| st.sidebar.image('Screenshot 2022-01-09 161732.png') | |
| st.sidebar.image('woman-showing-four-fingers-white-background-woman-showing-four-fingers-white-background-closeup-hand-134504006.jpg') | |
| st.sidebar.image('demo.jpg') | |
| hand_count =0 | |
| image = cv2.cvtColor(image,cv2.COLOR_RGB2BGR) | |
| cap = cv2.imread('demo.jpg', cv2.IMREAD_UNCHANGED) | |
| # xxx= image | |
| # xxx= f'{image}' | |
| # IMAGE_FILE.append(xxx) | |
| # plt.imshow(image_batch[i].numpy().astype("uint8")) | |
| # IMAGE_FILE.append(image) | |
| # image = cv2.imread(opencv_image, cv2.IMREAD_UNCHANGED) | |
| # IMAGE_FILES.append(image) | |
| with mp_hands.Hands( | |
| static_image_mode=True, | |
| max_num_hands=max_hands, | |
| min_detection_confidence=detection_confidence) as hands: | |
| hand_count+=1 | |
| # for idx, file in enumerate(IMAGE_FILES): | |
| # Read an image, flip it around y-axis for correct handedness output (see | |
| # above). | |
| # image = cv2.flip(cv2.imread(file), 1) | |
| # Convert the BGR image to RGB before processing. | |
| results = hands.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) | |
| # Print handedness and draw hand landmarks on the image. | |
| # int('Handedness:', results.multi_handedness) | |
| # if not results.multi_hand_landmarks: | |
| # continue | |
| try: | |
| age_height, image_width, _ = image.shape | |
| annotated_image = image.copy() | |
| lmList=[] | |
| lmList2forModel=[] | |
| for hand_landmarks in results.multi_hand_landmarks: | |
| # print('hand_landmarks:', hand_landmarks) | |
| # print( | |
| # f'Index finger tip coordinates: (', | |
| # f'{hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP].x * image_width}, ' | |
| # f'{hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP].y * image_height})' | |
| # ) | |
| myHands=results.multi_hand_landmarks[0] | |
| for id,lm in enumerate(myHands.landmark): | |
| h,w,c=image.shape | |
| cx,cy=int(lm.x*w), int(lm.y*h) | |
| lmList.append([id,cx,cy]) | |
| lmList2forModel.append([cx,cy]) | |
| fingers=[] | |
| if lmList[tipIds[0]][1] < lmList[tipIds[0]-1][1]: | |
| fingers.append(1) | |
| else: | |
| fingers.append(0) | |
| for id in range(1,5): | |
| if lmList[tipIds[id]][2] < lmList[tipIds[id]-1][2]: | |
| fingers.append(1) | |
| else: | |
| fingers.append(0) | |
| total= fingers.count(1) | |
| if total==5: | |
| # st.text('Acclerate') | |
| # st.subheader("Acclerate") | |
| # mmm=st.markdown("Acclerate") | |
| # st.markdown('---') | |
| original_title = '<p style="font-family:Arial Black; color:#FD0177; font-size: 30px;">Acclerate</p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| # st.markdown('---') | |
| overlay = cv2.imread('istockphoto-1179377734-612x612.jpg') | |
| overlay = cv2.resize(overlay,(100,100)) | |
| x_offset = 80 | |
| y_offset = 10 | |
| x_end = x_offset + overlay.shape[1] | |
| y_end = y_offset + overlay.shape[0] | |
| annotated_image[y_offset:y_end,x_offset:x_end] = overlay | |
| if total==4: | |
| # st.text('Right') | |
| original_title = '<p style="font-family:Arial Black; color:#FD0177; font-size: 30px;">Right</p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| overlay = cv2.imread('istockphoto-1179377734-612x612 (4).jpg') | |
| overlay = cv2.resize(overlay,(100,100)) | |
| x_offset = 120 | |
| y_offset = 50 | |
| x_end = x_offset + overlay.shape[1] | |
| y_end = y_offset + overlay.shape[0] | |
| annotated_image[y_offset:y_end,x_offset:x_end] = overlay | |
| if total==2 or total==3: | |
| # st.text('Left') | |
| original_title = '<p style="font-family:Arial Black; color:#FD0177; font-size: 30px;">Left</p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| overlay = cv2.imread('istockphoto-1179377734-612x612 (1).jpg') | |
| overlay = cv2.resize(overlay,(100,100)) | |
| x_offset = 50 | |
| y_offset = 50 | |
| x_end = x_offset + overlay.shape[1] | |
| y_end = y_offset + overlay.shape[0] | |
| annotated_image[y_offset:y_end,x_offset:x_end] = overlay | |
| if total==0: | |
| # st.text('Brake') | |
| original_title = '<p style="font-family:Arial Black; color:#FD0177; font-size: 30px;">Brake</p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| overlay = cv2.imread('istockphoto-1179377734-612x612 (3).jpg') | |
| overlay = cv2.resize(overlay,(100,100)) | |
| x_offset = 50 | |
| y_offset = 90 | |
| x_end = x_offset + overlay.shape[1] | |
| y_end = y_offset + overlay.shape[0] | |
| annotated_image[y_offset:y_end,x_offset:x_end] = overlay | |
| mp_drawing.draw_landmarks( | |
| annotated_image, | |
| hand_landmarks, | |
| mp_hands.HAND_CONNECTIONS, | |
| mp_draw.DrawingSpec(color=(0,0,255), thickness=2, circle_radius=2), | |
| mp_draw.DrawingSpec(color=(0,255,0), thickness=2, circle_radius=2)) | |
| # annotated_image= cv2.cvtColor(annotated_image,cv2.COLOR_BGR2RGB) | |
| kpi1_text.write(f"<h1 style='text-align: center; color:red; '>{hand_count}</h1>", unsafe_allow_html=True) | |
| # st.subheader('Output Image') | |
| # st.image(annotated_image, use_column_width=True) | |
| except TypeError: | |
| # st.text('Sorry No Hand Found!!') | |
| original_title = '<p style="font-family:Arial Black; color:Red; font-size: 30px;">Sorry, No Hand Found!!</p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| kpi1_text.write(f"<h1 style='text-align: center; color:red; '>{0}</h1>", unsafe_allow_html=True) | |
| # annotated_image= cv2.cvtColor(annotated_image,cv2.COLOR_BGR2RGB) | |
| # kpi1_text.write(f"<h1 style='text-align: center; color:red; '>{hand_count}</h1>", unsafe_allow_html=True) | |
| st.subheader('Output Image') | |
| annotated_image = cv2.cvtColor(annotated_image,cv2.COLOR_BGR2RGB) | |
| st.image(annotated_image, use_column_width=False) | |
| elif app_mode == 'Run On Video': | |
| st.set_option('deprecation.showfileUploaderEncoding',False) | |
| # st.text('This is some text.') | |
| # st.text('This is somext.') | |
| use_webcam = st.sidebar.button('Use Webcam') | |
| record= st.sidebar.checkbox("Record Video") | |
| if record: | |
| st.checkbox("Recording",value=True) | |
| # drawing_spec = mp_drawing.DrawingSpec(thickness=2, circle_radius=1) | |
| # st.sidebar.markdown ('---------' ) | |
| st.markdown( | |
| """ | |
| <style> | |
| [data-testid="stSidebar"][aria-expanded="true"] > div:first-child{ | |
| width: 350px | |
| } | |
| [data-testid="stSidebar"][aria-expanded="false"] > div:first-child{ | |
| width: 350px | |
| margin-left: -350px | |
| </style> | |
| """,unsafe_allow_html=True,) | |
| # st.markdown("**Detected Hands**") | |
| # kpi1_text = st.markdown("0") | |
| max_hands= st.sidebar.number_input('Maximum Number of Hand',value=1,min_value=1,max_value=4) | |
| # st.sidebar('---') | |
| detection_confidence= st.sidebar.slider('Detection Confidence',min_value=0.0,max_value=1.0,value=0.5) | |
| tracking_confidence= st.sidebar.slider('Tracking Confidence Confidence',min_value=0.0,max_value=1.0,value=0.5) | |
| st.sidebar.markdown('---') | |
| # st.markdown("Output") | |
| st.subheader("Input Video") | |
| stframe = st.empty() | |
| video_file_buffer = st.sidebar.file_uploader("Upload a Video", type=['mp4', 'mov', 'avi', 'asf', 'm4v']) | |
| tffile = tempfile.NamedTemporaryFile(delete=False) | |
| ##We get our input video here | |
| if not video_file_buffer: | |
| if use_webcam: | |
| vid = cv2.VideoCapture(0) | |
| else: | |
| vid = cv2.VideoCapture(DEMO_VIDEO) | |
| tffile.name = DEMO_VIDEO | |
| else: | |
| tffile.write(video_file_buffer.read()) | |
| vid = cv2.VideoCapture(tffile.name) | |
| width = int(vid.get(cv2.CAP_PROP_FRAME_WIDTH)) | |
| height = int(vid.get(cv2.CAP_PROP_FRAME_HEIGHT)) | |
| fps_input = int(vid.get(cv2.CAP_PROP_FPS)) | |
| #Recording Part | |
| codec = cv2.VideoWriter_fourcc('V', 'P', '0','9') | |
| out= cv2.VideoWriter('output.mp4',codec,fps_input,(width,height)) | |
| st.sidebar.text('Input Video') | |
| st.sidebar.video(tffile.name) | |
| # st.markdown('Reload , if webpage hangs') | |
| fps = 0 | |
| i = 0 | |
| drawing_spec = mp_drawing.DrawingSpec(thickness=2, circle_radius=1) | |
| kpi1, kpi2, kpi3 = st.columns(3) | |
| with kpi1: | |
| # st.markdown("**Frame Rate**") | |
| original_title = '<p style="text-align: center; font-size: 20px;"><strong>Frame Rate</strong></p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| kpi1_text = st.markdown ("0") | |
| with kpi2: | |
| # st.markdown("**Detected Hands**") | |
| original_title = '<p style="text-align: center; font-size: 20px;"><strong>Detected Hands</strong></p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| kpi2_text = st.markdown ("0") | |
| with kpi3: | |
| # st.markdown("**Width**") | |
| original_title = '<p style="text-align: center; font-size: 20px;"><strong>Video Width</strong></p>' | |
| st.markdown(original_title, unsafe_allow_html=True) | |
| kpi3_text = st.markdown("0") | |
| st.markdown ("<hr/>", unsafe_allow_html=True) | |
| st.subheader('Reload , if webpage hangs') | |
| drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1) | |
| # st.subheader("Input Video") | |
| with mp_hand.Hands(max_num_hands=max_hands,min_detection_confidence=detection_confidence, | |
| min_tracking_confidence=tracking_confidence) as hands: | |
| while vid.isOpened(): | |
| i +=1 | |
| ret, image = vid.read() | |
| # image.set(3, 640) | |
| # image.set(4, 480) | |
| if not ret: | |
| continue | |
| image.flags.writeable=False | |
| results= hands.process(image) | |
| image.flags.writeable=True | |
| image= cv2.cvtColor(image,cv2.COLOR_RGB2BGR) | |
| lmList=[] | |
| lmList2forModel=[] | |
| hand_count=0 | |
| if results.multi_hand_landmarks: | |
| # original_title = 'Acclerate' | |
| # Face Landmark Drawing | |
| for hand_landmark in results.multi_hand_landmarks: | |
| hand_count += 1 | |
| myHands=results.multi_hand_landmarks[0] | |
| for id,lm in enumerate(myHands.landmark): | |
| h,w,c=image.shape | |
| cx,cy=int(lm.x*w), int(lm.y*h) | |
| lmList.append([id,cx,cy]) | |
| lmList2forModel.append([cx,cy]) | |
| if lmList[tipIds[0]][1] > lmList[tipIds[0]-1][1]: | |
| fingers.append(1) | |
| else: | |
| fingers.append(0) | |
| for id in range(1,5): | |
| if lmList[tipIds[id]][2] < lmList[tipIds[id]-1][2]: | |
| fingers.append(1) | |
| else: | |
| fingers.append(0) | |
| total= fingers.count(1) | |
| # print('**********') | |
| # print(total) | |
| if total==5: | |
| # print('brake') | |
| # st.text('Acclerate') | |
| # original_title= 'Acc' | |
| sh= "Acclerate" | |
| draw(sh) | |
| if total==2 or total==3: | |
| sh= "Left" | |
| draw(sh) | |
| if total==4: | |
| sh= "Right" | |
| draw(sh) | |
| if total==0: | |
| sh= "Brake" | |
| draw(sh) | |
| # time.sleep(1) | |
| # original_title = '<p style="font-family:Arial Black; color:Blue; font-size: 30px;">{original_title}</p>' | |
| # st.markdown(original_title, unsafe_allow_html=True) | |
| mp_draw.draw_landmarks(image,hand_landmark,mp_hand.HAND_CONNECTIONS, | |
| mp_draw.DrawingSpec(color=(0,0,255), thickness=2, circle_radius=2), | |
| mp_draw.DrawingSpec(color=(0,255,0), thickness=2, circle_radius=2)) | |
| #FPS Counter Logic | |
| currTime = time.time() | |
| fps = 1/ (currTime - prevTime) | |
| prevTime = currTime | |
| fingers=[] | |
| if record: | |
| out.write(image) | |
| image= cv2.cvtColor(image,cv2.COLOR_BGR2RGB) | |
| kpi1_text.write(f"<h1 style='text-align: center; color:red; '>{int(fps)}</h1>", unsafe_allow_html=True) | |
| kpi2_text.write(f"<h1 style='text-align: center; color:red; '>{hand_count}</h1>", unsafe_allow_html=True) | |
| kpi3_text.write(f"<h1 style='text-align: center; color:red; '>{width}</h1>", unsafe_allow_html=True) | |
| image = cv2.resize(image, (0,0), fx = 0.8, fy =0.8) | |
| image = image_resize(image = image, width = 320,height=360) | |
| stframe.image(image, channels = 'BGR', use_column_width=False) | |
| # else: | |
| # output_video = open('output1.mp4','rb') | |
| # out_bytes= output_video.read() | |
| # st.video(out_bytes) | |
| st.subheader('Output Image') | |
| st.text('Video Processed') | |
| output_video = open('output1.mp4','rb') | |
| out_bytes= output_video.read() | |
| st.video(out_bytes) | |
| # st.markdown('Reload , if webpage hangs') | |
| vid.release() | |
| out.release() | |