Translate自学习
2023-04-20
| 更新时间 | 负责人 | 内容 | 备注 |
|---|---|---|---|
| 2022年1月4日 | Rui | 初次编写文档 | ---- |
| 2022年1月8日 | dianjixz | 修改文档的编写方式 | 使用 Jupyter notebook 进行编写文档 |
| 2022年1月18日 | Rui | 修改文档，增加效果图 | 通过测试的平台有 MaixII-Dock，使用的是 MaixPy3 0.4.0 |
运行效果
准备
- 在 MaixHub 上获取模型文件和运行源码（最新版本的系统内置了模型文件
/home/model/resnet18_1000_awnn*） - 确认 MaixPy3 版本为 0.4.3 以上
- 使用的硬件为 MaixII-Dock
- 内存卡内是最新版本的镜像系统
- 插卡启动硬件
自学习训练与保存
将模型读取到python环境中！
In [1]:
from maix import nn
from maix import camera, display
import time
class Self_learn:
model = {
"param": "/home/model/resnet18_1000_awnn.param",
"bin": "/home/model/resnet18_1000_awnn.bin"
}
options = {
"model_type": "awnn",
"inputs": {
"input0": (224, 224, 3)
},
"outputs": {
"190": (1, 1, 512)
},
"mean": [127.5, 127.5, 127.5],
"norm": [0.0176, 0.0176, 0.0176],
}
class_num = 3 #学习类别
sample_num = 15 #学习类别总数量
curr_class = 0
curr_sample = 0
def __init__(self):
from maix import nn
from maix.nn.app.classifier import Classifier
print("-- load model:", self.model)
self.m = nn.load(self.model, opt=self.options)
print("-- load ok")
print("-- load classifier")
self.classifier = Classifier(self.m, self.class_num, self.sample_num, 512, 224, 224)
print("-- load ok")
[ rpyc-kernel ]( running at Thu Jan 20 09:45:15 2022 )
-- load model: {'param': '/home/model/resnet18_1000_awnn.param', 'bin': '/home/model/resnet18_1000_awnn.bin'}
-- load ok
-- load classifier
-- load ok
In [1]:
import time
from maix import camera, display
self_learn = Self_learn()
for x in range(3):
t = time.time()
while True:
if (time.time() - t) > 2:
img = camera.capture().resize(224, 224)
self_learn.classifier.add_class_img(img)
display.show(img)
time.sleep(2)
print("add ok!")
break
img = camera.capture()
display.show(img)
add ok!
In [1]:
import time
from maix import nn
from maix import camera, display
for x in range(3):
t = time.time()
while True:
if (time.time() - t) > 2:
for i in range(5):
img = camera.capture().resize(224, 224)
self_learn.classifier.add_sample_img(img)
display.show(img)
time.sleep(2)
break
display.show(camera.capture())
进行图片自学习
In [1]:
self_learn.classifier.train()
print("train over")[ rpyc-kernel ]( running at Thu Jan 20 09:31:48 2022 )
训练结束后保存模型
In [1]:
self_learn.classifier.save("./module.bin")
print("save over")[ rpyc-kernel ]( running at Wed Jan 19 15:43:36 2022 )
开始进行分类验证
In [1]:
import time
from maix import nn
from maix import camera, display
while True:
img = camera.capture()
AI_img = img.copy().resize(224, 224)
idx, distance = self_learn.classifier.predict(AI_img)
msg = "predict class: " + str(idx+1) + ", conf: " + str(100-distance)
print(msg)
img.draw_string(10, 10, msg, color = (255, 0, 0))
display.show(img)
predict class: 2, conf: 88
Out[1]:
Traceback (most recent call last): File "<string>", line unknown, in <module> Remote.KeyboardInterrupt
In [1]:
class Self_learn:
model = {
"param": "/home/model/resnet18_1000_awnn.param",
"bin": "/home/model/resnet18_1000_awnn.bin"
}
options = {
"model_type": "awnn",
"inputs": {
"input0": (224, 224, 3)
},
"outputs": {
"190": (1, 1, 512)
},
"mean": [127.5, 127.5, 127.5],
"norm": [0.0176, 0.0176, 0.0176],
}
class_num = 3 #学习类别
sample_num = 15 #学习类别总数量
curr_class = 0
curr_sample = 0
def __init__(self):
from maix import nn
from maix.nn.app.classifier import Classifier
from maix.nn.app.classifier import load
import os.path
if os.path.isfile("./module.bin"):
print("-- load model:", self.model)
self.m = nn.load(self.model, opt=self.options)
print("-- load ok")
print("-- load classifier")
self.classifier = load(self.m,"./module.bin")
print("-- load ok")
else:
print("not have model!")
print("please run nn_self_learn_classifier.py get model!")
print(Self_learn)[ rpyc-kernel ]( running at Wed Jan 19 15:44:46 2022 )
-- load model: {'param': '/home/model/resnet18_1000_awnn.param', 'bin': '/home/model/resnet18_1000_awnn.bin'}
-- load ok
-- load classifier
-- load ok
自学习预测
In [1]:
import time
from maix import camera, display
self_learn = Self_learn()
while True:
img = camera.capture()
AI_img = img.copy().resize(224, 224)
idx, distance = self_learn.classifier.predict(AI_img)
msg = "predict class: " + str(idx+1) + ", conf: " + str(100-distance)
# print(msg)
img.draw_string(10, 10, msg, color = (255, 0, 0))
display.show(img)
Out[1]:
Traceback (most recent call last): File "<string>", line unknown, in <module> Remote.KeyboardInterrupt
