Micropython玩转ESP32P4：绑定AI相关模块
本帖最后由 PY学习笔记 于 2025-8-10 14:48 编辑近期，dfrobot出了一款新的开发板——FireBeetle 2 ESP32-P4，板载ESP32P4，虽然没有内置的WIFI和BLE，但是它的性能十分的高，所以很有幸能体验到这款开发板1.开发板介绍FireBeetle 2 ESP32-P4有很多种外设:
[*]Type-C USB CDC：Type-C USB烧录、调试接口
[*]IO3/LED：板载LED引脚
[*]Power LED：主板电源指示灯
[*]RST：复位按键
[*]IO35/BOOT：IO引脚/BOOT按键
[*]MIC: MEMS PDM麦克风
[*]HIGH-SPEED USB OTG 2.0: Type-C高速USB OTG 2.0
[*]ESP32-P4：ESP32-P4芯片
[*]MIPI-DSI: 两通道MIPI-DSI屏幕（兼容树莓派4B DSI屏幕线序）
[*]MIPI-CSI: 两通道MIPI-DSI屏幕（兼容树莓派4B CSI摄像头线序）
[*]TF Card: TF卡插槽
[*]16MB FLASH: 16MB Flash存储
[*]ESP32-C6：ESP32-C6-MINI-1模组，通过SDIO与ESP32-P4连接，用于扩展WiFi、蓝牙
https://img.dfrobot.com.cn/wikicn/5d57611a3416442fa39bffca/a5136d9f2426d7f157c92e378261d590.png2.绑定AI相关模块在github上面，有一个大佬分享了一个将EspDL绑定到micropython中，但是还少了一个猫咪识别的模型，所以自己做了一个，仓库地址如下：https://github.com/Vincent1-python/mp_esp_dl_models/tree/cat_detect接着需要将驱动也绑定进来，修改~/esp/micropython.cmake如下：include(${CMAKE_CURRENT_LIST_DIR}/micropython_csi_camera/micropython.cmake)
include(${CMAKE_CURRENT_LIST_DIR}/mp_jpeg/src/micropython.cmake)
include(${CMAKE_CURRENT_LIST_DIR}/mp_esp_dl_models/src/micropython.cmake)再次编译即可使用。3.体验AI相关模块首先是人脸检测：from espdl import FaceDetector
from jpeg import Decoder, Encoder
decoder = Decoder()
# 捕获并处理图像
img = open("human_face.jpg", "rb").read()# 捕获原始图像（通常是JPEG格式）
wh = decoder.get_img_info(img)# 获取图像的宽度和高度
# 获取图像的宽度和高度
width, height = wh
encoder = Encoder(width=width, height=height, pixel_format="RGB888")
face_detector = FaceDetector(width=width, height=height)
framebuffer = decoder.decode(img)# 转换为RGB888格式
# 将memoryview转换为bytearray以便修改
framebuffer = bytearray(framebuffer)
# 运行人脸检测
results = face_detector.run(framebuffer)
# 绘制边框
def draw_rectangle(buffer, width, height, x, y, w, h, list1, color=(255, 0, 0)):
"""
在RGB888格式的图像缓冲区上绘制矩形边框
:param buffer: 图像缓冲区
:param width: 图像宽度
:param height: 图像高度
:param x: 边框左上角的x坐标
:param y: 边框左上角的y坐标
:param w: 边框宽度
:param h: 边框高度
:param color: 边框颜色（RGB格式）
"""
# 辅助函数：设置单个像素的颜色
def set_pixel(buffer, width, x, y, color):
offset = (y * width + x) * 3
buffer = color# R
buffer = color# G
buffer = color# B
# 辅助函数：绘制更大的点
def draw_large_dot(buffer, width, x, y, color, size=3):
for i in range(x - size, x + size + 1):
for j in range(y - size, y + size + 1):
if 0 <= i < width and 0 <= j < height:
set_pixel(buffer, width, i, j, color)
# 绘制上边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y < height:
set_pixel(buffer, width, i, y, color)
# 绘制下边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y + h < height:
set_pixel(buffer, width, i, y + h, color)
# 绘制左边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x < width:
set_pixel(buffer, width, x, j, color)
# 绘制右边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x + w < width:
set_pixel(buffer, width, x + w, j, color)
# 绘制特征点
if list1:
draw_large_dot(buffer, width, list1, list1, (0, 0, 255), size=2)
draw_large_dot(buffer, width, list1, list1, (0, 0, 255), size=2)
draw_large_dot(buffer, width, list1, list1, (0, 255, 0), size=2)
draw_large_dot(buffer, width, list1, list1, (255, 0, 0), size=2)
draw_large_dot(buffer, width, list1, list1, (255, 0, 0), size=2)
if results:
# 在图像上绘制人脸边框
for face in results:
print(face)
x1, y1, x2, y2 = face['box']
draw_rectangle(framebuffer, width, height, x1, y1, x2 - x1, y2 - y1, face['features'], color=(255, 0, 0))# 使用红色边框
# 将带有边框的图像重新编码为JPEG格式并保存
marked_img = encoder.encode(framebuffer)
with open("marked_image.jpg", "wb") as f:
f.write(marked_img)</span>
行人检测：from espdl import HumanDetector
from jpeg import Decoder, Encoder
decoder = Decoder()
encoder = Encoder(width=640, height=480,pixel_format="RGB888")
human_detector = HumanDetector(width=640, height=480)
# 捕获并处理图像
img = open("pedestrian.jpg", "rb").read()# 捕获原始图像（通常是JPEG格式）
framebuffer = decoder.decode(img)# 转换为RGB888格式
# 将memoryview转换为bytearray以便修改
framebuffer = bytearray(framebuffer)
# 运行行人检测
results = human_detector.run(framebuffer)
# 绘制边框
def draw_rectangle(buffer, width, height, x, y, w, h, color=(255, 0, 0)):
"""
在RGB888格式的图像缓冲区上绘制矩形边框
:param buffer: 图像缓冲区
:param width: 图像宽度
:param height: 图像高度
:param x: 边框左上角的x坐标
:param y: 边框左上角的y坐标
:param w: 边框宽度
:param h: 边框高度
:param color: 边框颜色（RGB格式）
"""
# 辅助函数：设置单个像素的颜色
def set_pixel(buffer, width, x, y, color):
offset = (y * width + x) * 3
buffer = color# R
buffer = color# G
buffer = color# B
# 绘制上边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y < height:
set_pixel(buffer, width, i, y, color)
# 绘制下边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y + h < height:
set_pixel(buffer, width, i, y + h, color)
# 绘制左边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x < width:
set_pixel(buffer, width, x, j, color)
# 绘制右边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x + w < width:
set_pixel(buffer, width, x + w, j, color)
# 在图像上绘制边框
for face in results:
print(face)
x1, y1, x2, y2 = face['box']
draw_rectangle(framebuffer, 640, 480, x1, y1, x2-x1, y2-y1, color=(255, 0, 0))# 使用红色边框
# 将带有边框的图像重新编码为JPEG格式并保存
marked_img = encoder.encode(framebuffer)
with open("marked_image1.jpg", "wb") as f:
f.write(marked_img)
猫咪检测：from espdl import CatDetector
from jpeg import Decoder, Encoder
decoder = Decoder()
# 捕获并处理图像
img = open("cat.jpg", "rb").read()# 捕获原始图像（通常是JPEG格式）
wh = decoder.get_img_info(img)# 获取图像的宽度和高度
# 获取图像的宽度和高度
width, height = wh
encoder = Encoder(width=width, height=height, pixel_format="RGB888")
cat_detector = CatDetector(width=width, height=height)
framebuffer = decoder.decode(img)# 转换为RGB888格式
# 将memoryview转换为bytearray以便修改
framebuffer = bytearray(framebuffer)
# 运行猫咪检测
results = cat_detector.run(framebuffer)
# 绘制边框
def draw_rectangle(buffer, width, height, x, y, w, h, list1, color=(255, 0, 0)):
"""
在RGB888格式的图像缓冲区上绘制矩形边框
:param buffer: 图像缓冲区
:param width: 图像宽度
:param height: 图像高度
:param x: 边框左上角的x坐标
:param y: 边框左上角的y坐标
:param w: 边框宽度
:param h: 边框高度
:param color: 边框颜色（RGB格式）
"""
# 辅助函数：设置单个像素的颜色
def set_pixel(buffer, width, x, y, color):
offset = (y * width + x) * 3
buffer = color# R
buffer = color# G
buffer = color# B
# 辅助函数：绘制更大的点
def draw_large_dot(buffer, width, x, y, color, size=3):
for i in range(x - size, x + size + 1):
for j in range(y - size, y + size + 1):
if 0 <= i < width and 0 <= j < height:
set_pixel(buffer, width, i, j, color)
# 绘制上边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y < height:
set_pixel(buffer, width, i, y, color)
# 绘制下边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y + h < height:
set_pixel(buffer, width, i, y + h, color)
# 绘制左边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x < width:
set_pixel(buffer, width, x, j, color)
# 绘制右边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x + w < width:
set_pixel(buffer, width, x + w, j, color)
# 绘制特征点
if list1:
draw_large_dot(buffer, width, list1, list1, (0, 0, 255), size=2)
draw_large_dot(buffer, width, list1, list1, (0, 0, 255), size=2)
draw_large_dot(buffer, width, list1, list1, (0, 255, 0), size=2)
draw_large_dot(buffer, width, list1, list1, (255, 0, 0), size=2)
draw_large_dot(buffer, width, list1, list1, (255, 0, 0), size=2)
if results:
# 在图像上绘制边框
for face in results:
print(face)
x1, y1, x2, y2 = face['box']
draw_rectangle(framebuffer, width, height, x1, y1, x2 - x1, y2 - y1, None, color=(255, 0, 0))# 使用红色边框
# 将带有边框的图像重新编码为JPEG格式并保存
marked_img = encoder.encode(framebuffer)
with open("marked_image4.jpg", "wb") as f:
f.write(marked_img)
yolo11分类：from espdl import CocoDetector
from jpeg import Decoder, Encoder
from myufont import CustomBMFont
from machine import Pin,SDCard
import os
sd = SDCard(slot=0,width=4, sck=43, cmd=44, data=(39, 40, 41, 42))
os.mount(sd, '/sd')
decoder = Decoder()
encoder = Encoder(width=405, height=540,pixel_format="RGB888")
face_detector = CocoDetector(width=405, height=540)
MSCOCO_CLASSES = [
"人", "自行车", "汽车", "摩托车", "飞机", "公共汽车", "火车", "卡车", "船", "交通灯",
"消防栓", "消防水带", "停车计时器", "长椅", "鸟", "猫", "狗", "马", "羊", "牛",
"大象", "熊", "斑马", "长颈鹿", "背包", "伞", "手提包", "领带", "行李箱", "飞盘",
"滑雪板", "滑雪杖", "滑板", "冲浪板", "网球拍", "瓶子", "酒杯", "杯子", "刀叉", "碗",
"香蕉", "苹果", "三明治", "橙子", "西兰花", "胡萝卜", "热狗", "披萨", "甜甜圈", "蛋糕",
"椅子", "沙发", "盆栽", "床", "餐桌", "马桶", "电视", "笔记本电脑", "鼠标", "遥控器",
"键盘", "手机", "微波炉", "烤箱", "烤面包机", "水槽", "冰箱", "书", "时钟", "花瓶",
"剪刀", "泰迪熊", "吹风机", "牙刷"
]
font = CustomBMFont('/sd/text_full_16px_2312.v3.bmf')
# 捕获并处理图像
img = open("bus.jpg", "rb").read()# 捕获原始图像（通常是JPEG格式）
framebuffer = decoder.decode(img)# 转换为RGB888格式
# 将memoryview转换为bytearray以便修改
framebuffer = bytearray(framebuffer)
# 运行人脸检测
results = face_detector.run(framebuffer)
# 绘制边框
def draw_rectangle(buffer, width, height, x, y, w, h,font,label, color=(255, 0, 0)):
"""
在RGB888格式的图像缓冲区上绘制矩形边框
:param buffer: 图像缓冲区
:param width: 图像宽度
:param height: 图像高度
:param x: 边框左上角的x坐标
:param y: 边框左上角的y坐标
:param w: 边框宽度
:param h: 边框高度
:param color: 边框颜色（RGB格式）
"""
# 辅助函数：设置单个像素的颜色
def set_pixel(buffer, width, x, y, color):
offset = (y * width + x) * 3
buffer = color# R
buffer = color# G
buffer = color# B
def is_chinese(ch):
"""判断一个字符是否为中文字符"""
if '\u4e00' <= ch <= '\u9fff' or \
'\u3400' <= ch <= '\u4dbf' or \
'\u20000' <= ch <= '\u2a6df':
return True
return False
def text(font, text, x_start, y_start, color,spacing=0, line_spacing=0, max_width=width):
font_size = font.font_size
bytes_per_row = (font_size + 7) // 8# 每行占用的字节数
x, y = x_start, y_start
for char in text:
# 处理换行符
if char == '\n':
y += font_size + line_spacing
x = x_start
continue
if char == '\r':
x += 2*font_size
continue
# 获取字符宽度(中文字符全宽，ASCII字符半宽)
char_width = font_size if is_chinese(char) else font_size // 2
# 检查是否需要换行
if max_width is not None and x + char_width > x_start + max_width:
y += font_size + line_spacing
x = x_start
# 获取字符位图
bitmap = font.get_char_bitmap(char)
# 绘制字符
for row in range(font_size):
for col in range(char_width if not is_chinese(char) else font_size):
byte_idx = row * bytes_per_row + col // 8
bit_mask = 0x80 >> (col % 8)
if byte_idx < len(bitmap) and (bitmap & bit_mask):
set_pixel(framebuffer,max_width,x + col, y + row, color)
# 移动到下一个字符位置
x += char_width + spacing
# 绘制上边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y < height:
set_pixel(buffer, width, i, y, color)
# 绘制下边框
for i in range(x, x + w):
if 0 <= i < width and 0 <= y + h < height:
set_pixel(buffer, width, i, y + h, color)
# 绘制左边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x < width:
set_pixel(buffer, width, x, j, color)
# 绘制右边框
for j in range(y, y + h):
if 0 <= j < height and 0 <= x + w < width:
set_pixel(buffer, width, x + w, j, color)
text(font,label, x, y-20, color)
# 在图像上绘制人脸边框
for face in results:
#print(face)
x1, y1, x2, y2 = face['box']
label = MSCOCO_CLASSES]+":"+str(int(face['score']*100))+"%"
draw_rectangle(framebuffer, 405, 540, x1, y1, x2-x1, y2-y1,font,label)# 使用红色边框
print(label)
# 将带有边框的图像重新编码为JPEG格式并保存
marked_img = encoder.encode(framebuffer)
with open("marked_image2.jpg", "wb") as f:
f.write(marked_img)
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