在opencv使用Jupyter代码写一个图片识别程序

以下是一个基础的图片识别程序，可以通过改变模型和图片来进行不同的识别任务。

首先，我们需要导入必要的库和模型：

import cv2
import matplotlib.pyplot as plt
import numpy as np

# 导入模型
model = cv2.dnn.readNetFromCaffe('models/deploy.prototxt', 'models/res10_300x300_ssd_iter_140000_fp16.caffemodel')

然后，我们选择一张图片进行识别：

image = cv2.imread('images/test.jpg')
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
plt.imshow(image)
plt.show()

接下来，我们对图片进行预处理，并使用模型进行识别：

# 预处理图片
blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))

# 使用模型进行识别
model.setInput(blob)
detections = model.forward()

最后，我们将识别结果绘制在图片上并展示：

# 绘制识别结果
for i in range(detections.shape[2]):
    confidence = detections[0, 0, i, 2]
    if confidence > 0.5:
        box = detections[0, 0, i, 3:7] * np.array([image.shape[1], image.shape[0], image.shape[1], image.shape[0]])
        (startX, startY, endX, endY) = box.astype("int")
        label = '{:.2f}%'.format(confidence * 100)
        cv2.rectangle(image, (startX, startY), (endX, endY), (0, 255, 0), 2)
        y = startY - 15 if startY - 15 > 15 else startY + 15
        cv2.putText(image, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

# 展示结果
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
plt.imshow(image)
plt.show()

完整代码如下：

import cv2
import matplotlib.pyplot as plt
import numpy as np

# 导入模型
model = cv2.dnn.readNetFromCaffe('models/deploy.prototxt', 'models/res10_300x300_ssd_iter_140000_fp16.caffemodel')

# 读取图片
image = cv2.imread('images/test.jpg')
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
plt.imshow(image)
plt.show()

# 预处理图片
blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))

# 使用模型进行识别
model.setInput(blob)
detections = model.forward()

# 绘制识别结果
for i in range(detections.shape[2]):
    confidence = detections[0, 0, i, 2]
    if confidence > 0.5:
        box = detections[0, 0, i, 3:7] * np.array([image.shape[1], image.shape[0], image.shape[1], image.shape[0]])
        (startX, startY, endX, endY) = box.astype("int")
        label = '{:.2f}%'.format(confidence * 100)
        cv2.rectangle(image, (startX, startY), (endX, endY), (0, 255, 0), 2)
        y = startY - 15 if startY - 15 > 15 else startY + 15
        cv2.putText(image, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

# 展示结果
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
plt.imshow(image)
plt.show()