Upload app.py

app.py

@@ -0,0 +1,117 @@
+# import basic libraries
+import numpy as np
+import streamlit as st
+import cv2
+from deepface import DeepFace as dfc
+from PIL import Image
+import os
+
+st.set_page_config(page_title='Face-detection-analysis', page_icon=None, layout='centered', initial_sidebar_state='auto')
+
+# function to load image
+try:
+    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+except Exception:
+    st.write("Error loading cascade classifiers")
+
+@st.cache
+def face_detect(img):
+    img = np.array(img.convert("RGB"))
+    face = face_cascade.detectMultiScale(image=img)
+
+    # draw rectangle around face
+    for (x, y, w, h) in face:
+        cv2.rectangle(img=img, pt1=(x, y), pt2=(x + w, y + h), color=(255, 0, 0), thickness=2)
+        roi = img[y:y + h, x:x + w]
+    return img, face
+
+# analyze image
+def analyze_image(img):
+    prediction = dfc.analyze(img_path=img)
+    return prediction
+
+#function for webcam
+def detect_web(image):
+
+    faces = face_cascade.detectMultiScale(
+        image=image, scaleFactor=1.3, minNeighbors=5)
+
+    for (x, y, w, h) in faces:
+        cv2.rectangle(img=image, pt1=(x, y), pt2=(
+            x + w, y + h), color=(255, 0, 0), thickness=2)
+    return image, faces
+
+def main():
+    # Face Analysis Application #
+    st.markdown("<h1 style='text-align: center;'>Face Detection and Analysis </h1>", unsafe_allow_html=True)
+    activiteis = ["Home", "Analyze Face", "About"]
+    choice = st.sidebar.selectbox("Select Activity", activiteis)
+    st.sidebar.markdown(
+        """ Developed by [Vivek] (https://github.com/7Vivek)""")
+    st.sidebar.markdown(
+        """ Checkout complete project [here] (https://github.com/7Vivek/Face-detection-analysis)""")
+    # C0C0C0
+    if choice == "Home":
+        html_temp_home1 = """<div style="background-color:#1E2839;padding:10px">
+                                            <h4 style="color:white;text-align:center;">
+                                            Face detection and Face feature analysis application using OpenCV, DeepFace and Streamlit.</h4>
+                                            </div>
+                                            </br>"""
+        st.image('https://cdn.dribbble.com/users/1373613/screenshots/5510801/media/b82469d51c432c2ff65c0158334cfabf.gif',use_column_width=True)
+        st.markdown(html_temp_home1, unsafe_allow_html=True)
+        st.write("""
+                 Application Functionalities.
+                 
+                 1. Face feature analysis such as emotion, gender and age.""")
+    elif choice == "Analyze Face":
+        st.subheader("Analyze facial features such as emotion, age and gender.")
+        image_file = st.file_uploader("Upload image you want to analyze", type=['jpg', 'png', 'jpeg'])
+
+        if image_file is not None:
+            #read image using PIL
+            image_loaded = Image.open(image_file)
+            #detect faces in image
+            result_img, result_face = face_detect(image_loaded)
+            st.image(result_img, use_column_width=True)
+            st.success("found {} face\n".format(len(result_face)))
+
+            if st.button("Analyze image"):
+                # convert image to array
+                new_image = np.array(image_loaded.convert('RGB'))
+                img = cv2.cvtColor(new_image, 1)
+                gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+                #analyze features of face
+                result = analyze_image(img)
+                # st.write(result)
+                st.write("Analysis summary")
+                st.write("Face emotion is ", result["dominant_emotion"], "in image.")
+                st.write("Gender recognized as", result["gender"], "in image.")
+                st.write("Age is", result["age"], "years.")
+            else:
+                pass
+                #st.write("Click on Analyze image ")
+
+    elif choice == "About":
+        st.subheader("About this app")
+        html_temp_about1= """<div style="background-color:#283347;padding:10px">
+                                    <h4 style="color:white;text-align:center;">
+                                    Face detection and Face feature analysis application using OpenCV, DeepFace and Streamlit.</h4>
+                                    </div>
+                                    </br>"""
+        st.markdown(html_temp_about1, unsafe_allow_html=True)
+
+        html_temp4 = """
+                             		<div style="background-color:#434E61;padding:10px">
+                             		<h4 style="color:white;text-align:center;">This Application is developed by Vivek Limbad using Streamlit Framework, Opencv and DeepFace library for demonstration purpose. If you have any suggestion or want to comment just write a mail at [email protected]. </h4>
+                             		<h4 style="color:white;text-align:center;">Thanks for Visiting </h4>
+                             		</div>
+                             		<br></br>
+                             		<br></br>"""
+
+        st.markdown(html_temp4, unsafe_allow_html=True)
+
+    else:
+        pass
+
+if __name__ == '__main__':
+    main()