CocoPi_upgrade/preset/app/15_faceDetection.py

#!/usr/bin/env python
#version    :       2023.12.31
#language   :       ch
from maix import camera
from maix import display

from maix import image

from maix import nn
from maix.nn import decoder

import os
ScreenOrientation = False
try:
    if os.path.exists("/etc/cameraSize.cfg"):
        cameraSize = True
    else:
        cameraSize = False
except:
    cameraSize = False
def getLcdRotation(cameraCapture):
    global cameraSize
    if cameraSize:
        return lcdRotationNew(cameraCapture)
    else:
        return lcdRotation(cameraCapture)

def lcdRotationNew(inputImg):
    global cameraSize,ScreenOrientation
    imageRotationBuffer = inputImg.crop(0, 0, 320, 240)
    if ScreenOrientation:
        imgRotationAim = image.new(size = (240, 320))
        rotationAngle = 90
        GETROTATION = imageRotationBuffer.rotate(+rotationAngle, adjust=1)
    else:
        imgRotationAim = image.new(size = (320, 240))
        GETROTATION = imageRotationBuffer

    GETROTATION = imgRotationAim.draw_image(GETROTATION,0,0,alpha=1)
    return GETROTATION

def lcdRotation(inputImg):
    global cameraSize,ScreenOrientation
    imageRotationBuffer = inputImg.crop(0, 0, 240, 320)
    if ScreenOrientation:
        imgRotationAim = image.new(size = (240, 320))
        rotationAngle = 180
    else:
        imgRotationAim = image.new(size = (320, 240))
        rotationAngle = 90
    GETROTATION = imageRotationBuffer.rotate(+rotationAngle, adjust=1)
    GETROTATION = imgRotationAim.draw_image(GETROTATION,0,0,alpha=1)
    return GETROTATION
   
if cameraSize==True:
    camera.camera.config(size=(320,240))
else:
    camera.camera.config(size=(240,320))

image.load_freetype("/root/preset/fonts/SourceHanSansCN-Regular.otf")

model = {
    "param": "/root/preset/model/yolo2_face_awnn.param",
    "bin": "/root/preset/model/yolo2_face_awnn.bin"
}
labels = ["person"]
options = {
    "model_type":  "awnn",
    "inputs": {
        "input0": (224, 224, 3)
    },
    "outputs": {
        "output0": (7, 7, (1+4+len(labels))*5)
    },
    "mean": [127.5, 127.5, 127.5],
    "norm": [0.0078125, 0.0078125, 0.0078125],
}
anchors = [1.19, 1.98, 2.79, 4.59, 4.53, 8.92, 8.06, 5.29, 10.32, 10.65]
m = nn.load(model, opt=options)
yolo2_decoder = decoder.Yolo2(len(labels), anchors, net_in_size=(options["inputs"]["input0"][0], options["inputs"]["input0"][1]), net_out_size=(7, 7))


canvasImg = image.new(size = (240, 320))
while True:
    canvasImg.clear()
    img_facedetection = getLcdRotation(camera.capture())
    img_facedetection = img_facedetection.crop(0, 0,224, 224)
    out = m.forward(img_facedetection.tobytes(), quantize=True, layout="hwc")
    boxes, probs = yolo2_decoder.run(out, nms=0.3, threshold=0.3, img_size=(options["inputs"]["input0"][0], options["inputs"]["input0"][1]))
    if len(boxes):
        for i in (boxes):
            img_facedetection.draw_rectangle(i[0],i[1], int(i[0]+i[2]),int(i[1]+i[3]), color=(255,0,0), thickness=1)
    canvasImg.draw_image(img_facedetection,48,8)
    canvasImg.draw_image(image.open("/root/preset/img/exit_ff0000_24x24.png"),288,216,alpha=1)
    display.show(canvasImg)