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react_to_my_face.py
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import io
import picamera # Camera
from pycoral.adapters import common
from pycoral.utils.edgetpu import make_interpreter
#### THIS IS IMPORTANT FOR LIFE STREAMING ####
import logging
import socketserver
from threading import Condition
from http import server
#### THIS IS IMPORTANT FOR IMAGE PROCESSING ####
import numpy as np
import cv2
PAGE="""\
<html>
<head>
<title>picamera MJPEG streaming demo</title>
</head>
<body>
<img src="stream.mjpg" width="640" height="480" style="width:100%;height:100%;" />
</body>
</html>
"""
class StreamingOutput(object):
def __init__(self):
self.frame = None
self.buffer = io.BytesIO()
self.condition = Condition()
def write(self, buf):
if buf.startswith(b'\xff\xd8'):
# New frame, copy the existing buffer's content and notify all
# clients it's available
self.buffer.truncate()
with self.condition:
self.frame = self.buffer.getvalue()
self.condition.notify_all()
self.buffer.seek(0)
return self.buffer.write(buf)
class StreamingHandler(server.BaseHTTPRequestHandler):
frame_i = 0
def do_GET(self):
if self.path == '/':
self.send_response(301)
self.send_header('Location', '/index.html')
self.end_headers()
elif self.path == '/index.html':
content = PAGE.encode('utf-8')
self.send_response(200)
self.send_header('Content-Type', 'text/html')
self.send_header('Content-Length', len(content))
self.end_headers()
self.wfile.write(content)
elif self.path == '/stream.mjpg':
self.send_response(200)
self.send_header('Age', 0)
self.send_header('Cache-Control', 'no-cache, private')
self.send_header('Pragma', 'no-cache')
self.send_header('Content-Type', 'multipart/x-mixed-replace; boundary=FRAME')
self.end_headers()
det = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
# This is where you specify the Deep Neural Network.
# Please put it in the same folder as the python file.
# --> this can go at the very beginning after import cv2 in the streaming file
interpreter = make_interpreter('face_edgetpu.tflite')
interpreter.allocate_tensors()
try:
while True:
with output.condition:
output.condition.wait()
frame = output.frame
#gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
### The image is encoded in bytes,
### needs to be converted to e.g. numpy array
frame = cv2.imdecode(np.frombuffer(frame, dtype=np.uint8),
cv2.IMREAD_COLOR)
rects = det.detectMultiScale(frame, scaleFactor=1.1, minNeighbors=5, minSize=(200, 200), flags=cv2.CASCADE_SCALE_IMAGE)
if rects is not None:
#### --> needs to happen for each image ####
# This resizes the RGB image
for (x, y, w, h) in rects:
crop_image = frame[y:y+h, x:x+w]
dim = (128,128)
resized_img = cv2.resize(crop_image, dim, interpolation = cv2.INTER_AREA)
resized_img = cv2.resize(resized_img, common.input_size(interpreter))
# Send resized image to Coral
common.set_input(interpreter, resized_img)
# Do the job
interpreter.invoke()
# Get the pose
print(interpreter.invoke())
if interpreter.invoke() is not None:
pose = common.output_tensor(interpreter, 0)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 20)
else:
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 20)
###############
## HERE CAN GO ALL IMAGE PROCESSING
###############
### and now we convert it back to JPEG to stream it
_, frame = cv2.imencode('.JPEG', frame)
self.wfile.write(b'--FRAME\r\n')
self.send_header('Content-Type', 'image/jpeg')
self.send_header('Content-Length', len(frame))
self.end_headers()
self.wfile.write(frame)
self.wfile.write(b'\r\n')
except Exception as e:
logging.warning(
'Removed streaming client %s: %s',
self.client_address, str(e))
else:
self.send_error(404)
self.end_headers()
class StreamingServer(socketserver.ThreadingMixIn, server.HTTPServer):
allow_reuse_address = True
daemon_threads = True
# Open the camera and stream a low-res image (width 640, height 480 px)
with picamera.PiCamera(resolution='640x480', framerate=24) as camera:
camera.vflip = True # Flips image vertically, depends on your camera mounting
camera.awb_gains = (1.2, 1.5)
camera.awb_mode = 'off'
output = StreamingOutput()
camera.start_recording(output, format='mjpeg')
try:
address = ('', 8000) # port 8000
server = StreamingServer(address, StreamingHandler)
server.serve_forever()
finally:
camera.stop_recording()