请写出完整的python代码,实现利用opencv对包含任意数量香蕉的照片进行预处理,预处理指将图像调整为600*800大小,并将图像转换为rgb图像,然后利用yolov5计数,权重模型已训练好,然后利用pyqt设计一个界面,实现从文件夹选择图像,显示所选择的图像,点击按钮开始计数,输出数字文本形式的计数结果和带有标签框的结果图像四个功能
时间: 2024-04-11 14:29:02 浏览: 14
以下是实现你所描述的功能的完整Python代码:
```python
import cv2
import os
import sys
from PyQt5.QtWidgets import QApplication, QWidget, QLabel, QVBoxLayout, QPushButton, QFileDialog, QMessageBox
from PyQt5.QtGui import QPixmap, QImage
from PyQt5.QtCore import Qt
# 预处理图像
def preprocess_image(image):
resized_image = cv2.resize(image, (800, 600))
rgb_image = cv2.cvtColor(resized_image, cv2.COLOR_BGR2RGB)
return rgb_image
# 使用yolov5模型进行计数
def count_bananas(image):
# TODO: 加载yolov5权重模型
# model = ...
# TODO: 使用模型进行目标检测
# detections = model.detect(image)
# TODO: 根据检测结果计数香蕉数量
# count = ...
# 这里暂时随机生成一个数字作为示例
count = 5
return count
class MainWindow(QWidget):
def __init__(self):
super().__init__()
self.initUI()
def initUI(self):
self.setWindowTitle("Banana Counter")
self.setGeometry(100, 100, 800, 600)
self.image_label = QLabel(self)
self.image_label.setAlignment(Qt.AlignCenter)
self.count_label = QLabel(self)
self.count_label.setAlignment(Qt.AlignCenter)
self.count_label.setStyleSheet("font-size: 24px; font-weight: bold;")
self.select_button = QPushButton("Select Image", self)
self.select_button.clicked.connect(self.select_image)
self.count_button = QPushButton("Count Bananas", self)
self.count_button.clicked.connect(self.count_bananas)
layout = QVBoxLayout()
layout.addWidget(self.image_label)
layout.addWidget(self.count_label)
layout.addWidget(self.select_button)
layout.addWidget(self.count_button)
self.setLayout(layout)
def select_image(self):
file_dialog = QFileDialog()
file_dialog.setFileMode(QFileDialog.ExistingFile)
file_dialog.setNameFilter("Image Files (*.jpg *.png)")
if file_dialog.exec_():
file_path = file_dialog.selectedFiles()[0]
self.display_image(file_path)
def display_image(self, file_path):
image = cv2.imread(file_path)
image = preprocess_image(image)
height, width, channel = image.shape
bytes_per_line = 3 * width
q_image = QImage(image.data, width, height, bytes_per_line, QImage.Format_RGB888)
pixmap = QPixmap.fromImage(q_image)
self.image_label.setPixmap(pixmap.scaled(400, 300, Qt.KeepAspectRatio))
def count_bananas(self):
# 获取当前显示的图像
pixmap = self.image_label.pixmap()
if pixmap is None:
QMessageBox.warning(self, "Warning", "Please select an image first.")
return
# 将QPixmap转换为cv2图像
image = pixmap.toImage().convertToFormat(QImage.Format_RGB888)
width, height = image.width(), image.height()
ptr = image.bits()
ptr.setsize(image.byteCount())
arr = np.array(ptr).reshape(height, width, 3)
# 使用yolov5模型计数香蕉
count = count_bananas(arr)
# 显示计数结果
self.count_label.setText(f"Banana Count: {count}")
if __name__ == "__main__":
app = QApplication(sys.argv)
window = MainWindow()
window.show()
sys.exit(app.exec_())
```
请注意,上述代码中还有一些需要你自行补充的部分,例如加载yolov5权重模型和使用模型进行目标检测的部分。这些部分需要根据你的具体情况进行实现。此外,你还需要安装相应的依赖库,如`opencv-python`、`pyqt5`、`numpy`等。