Added App

requirements.txt

@@ -0,0 +1,7 @@
+streamlit==1.3.1
+numpy
+pandas
+opencv-python-headless
+Pillow==8.3.2
+temp
+mediapipe==0.8.7

st2.py

@@ -0,0 +1,549 @@
+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')
+
+@st.cache ()
+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('360_F_61499604_hkfPSZ4ZYs47Yp8H780DEb3I3cvWjdmH.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()
+    
+
+            
+        
+        
+        
+            
+        

tempCodeRunnerFile.py

@@ -0,0 +1,2 @@
+
+        #     fingers.appen