facedetection.py

import cv2
import os
import io
import streamlit as st
import mediapipe as mp
import cv2 as cv
import numpy as np
import tempfile
import time
from PIL import Image

st.set_page_config(layout="wide")
st.session_state.setdefault("rows", {})
import analysis

DEMO_IMAGE = 'demo/demo.jpg'
DEMO_VIDEO = 'demo/demo.mp4'

left_placeholder, empty_placeholder, right_placeholder = st.columns([10, 1, 4])
video_frame_placeholder = st.empty()
video_text_placeholder = st.empty()
with left_placeholder:
	st.title('Face Detection with Mediapipe')

## Add Sidebar and Main Window style
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,
)

## Create Sidebar
st.sidebar.title('Selection')

# Add Debug Mode selection
debug_mode = st.sidebar.radio(
    "Select Debug Mode",
    ('Off', 'On')
)


st.sidebar.subheader('Parameter')

def main():
	## Define available pages in selection box
	app_mode = st.sidebar.selectbox(
	    'App Mode',
	    ['Image','Video','About']
	)
	
	# About Page
	if app_mode == 'About':
		image = Image.open('about.png')
		col1, col2 = st.columns([1, 2])
		
		with col1:
			# Display the image in the first column
			st.markdown(
				"""
					<style>
						.image-container {
						    margin-top: 50px;  
						}
					</style>
					<div class="image-container">
					<img src="about.png" alt="">
					</div>
				""", unsafe_allow_html=True
)
			st.image(image, caption='')

		with col2:
			# Display the About message in the second column
			st.write("""
				## About VisualAI
				The purpose of this application is to interprete the states of faces in a scenario with persons
				to feed this to loacal LLM AI interfaced by Langchain.\n 
				**Google Mediapipe** is used to perform this. **Streamlit** is used for the media interface (GUI).\n
				- **Martin Hummel**,\n
				  Senior Software Engineer,\n
				  Germany/Bavaria/Regensburg\n
				- Email: jupp@linuxmail.org\n	
				- [Github](https://github.com/MartinsRepo/VisualAI) \n
				**Dec. 2023**
			""")

	# Image Page
	elif app_mode == 'Image':
	
		# cleanup
		st.cache_data.clear()
		st.cache_resource.clear()
		
		left_placeholder, empty_placeholder, right_placeholder = st.columns([2, 1, 4])	

		st.sidebar.markdown('---')

		## Add Sidebar and Window style
		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,
		)

		max_faces = st.sidebar.number_input('Maximum Number of Faces', value=3, min_value=1, max_value=5)
		st.sidebar.markdown('---')

		detection_confidence = st.sidebar.slider('Min Detection Confidence', min_value=0.0,max_value=1.0,value=0.5)
		st.sidebar.markdown('---')

		## Output
		with left_placeholder:
			st.markdown('## Output Image')
			
		img_file_buffer = st.sidebar.file_uploader("Upload an Image", type=["jpg","jpeg","png"])
		
		if img_file_buffer is not None:
			image = np.array(Image.open(img_file_buffer))
			uploaded_file = io.TextIOWrapper(img_file_buffer) # retrieve uploaded filename
		else:
			demo_image = DEMO_IMAGE
			image = np.array(Image.open(demo_image))

		st.sidebar.text('Original Image')
		st.sidebar.image(image)

		face_count=0

		## Dashboard
		with mp.solutions.face_mesh.FaceMesh(
			static_image_mode=True, #Set of unrelated images
			max_num_faces=max_faces,
			min_detection_confidence=detection_confidence,
			refine_landmarks=False,
			min_tracking_confidence=0.01
		) as face_mesh:

			results = face_mesh.process(image)
			out_image=image.copy()
			
			if img_file_buffer is None:
				imgfilename = "demo.jpg"
			else:
				imgfilename = uploaded_file.name

			analysis.decode_image_mediapipe( out_image, imgfilename, results, face_count, left_placeholder, right_placeholder, debug_mode)
		
	# Video Page
	elif app_mode == 'Video':
		
		# Selector for video interface number
		video_interface_number = st.sidebar.number_input('Select Video Interface Number', min_value=0, value=0, step=1)
		use_webcam = st.sidebar.button('Use Webcam')
		record = st.sidebar.checkbox("Record Video")

		if record:
			st.checkbox('Recording', True)

		st.sidebar.markdown('---')

		## Add Sidebar and Window style
		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,
		)

		max_faces = st.sidebar.number_input('Maximum Number of Faces', value=2, min_value=1, max_value=5)
		st.sidebar.markdown('---')
		detection_confidence = st.sidebar.slider('Min Detection Confidence', min_value=0.0,max_value=1.0,value=0.5)
		tracking_confidence = st.sidebar.slider('Min Tracking Confidence', min_value=0.0,max_value=1.0,value=0.5)
		st.sidebar.markdown('---')

		## Get Video	
		video_file_buffer = st.sidebar.file_uploader("Upload a Video", type=['mp4', 'mov', 'avi'])
		temp_file = tempfile.NamedTemporaryFile(delete=False)

		if not video_file_buffer:
			if use_webcam:
				video = cv.VideoCapture(video_interface_number)
			else:
				video = cv.VideoCapture(DEMO_VIDEO)
				temp_file.name = DEMO_VIDEO

		else:
			temp_file.write(video_file_buffer.read())
			video = cv.VideoCapture(temp_file.name)

		width = int(video.get(cv.CAP_PROP_FRAME_WIDTH))
		height = int(video.get(cv.CAP_PROP_FRAME_HEIGHT))
		fps_input = int(video.get(cv.CAP_PROP_FPS))

		## Recording
		codec = cv.VideoWriter_fourcc(*"mp4v")
		out = cv.VideoWriter('output.mp4', codec, fps_input, (width,height))

		st.sidebar.text('Input Video')
		st.sidebar.video(temp_file.name)

		fps = 0
		i = 0
		
		analysis.decode_video_mediapipe(video, max_faces, detection_confidence, tracking_confidence, debug_mode)

		try:
			os.remove('output.mp4')
		except OSError as e:
			# If it fails, inform the user.
			print("Error: %s - %s." % (e.filename, e.strerror))

                
if __name__ == "__main__":
	main()