.

.gitignore

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+env/
+*.pyc
+__pycache__/

Dockerfile

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+# Выбор базового образа с предустановленным Python
+FROM python:3.9-slim
+
+# Установка неинтерактивного режима для APT (автоматический выбор ответов по умолчанию)
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Настройка временной зоны (пример для часовой зоны Москва)
+ENV TZ=Europe/Moscow
+RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
+
+# Обновление списка пакетов и установка необходимых системных зависимостей
+RUN apt-get update && apt-get install -y \
+    git \
+    python3-opencv \
+    # Удаление списков пакетов после установки для уменьшения размера образа
+    && rm -rf /var/lib/apt/lists/*
+
+# Копирование файла требований зависимостей Python в контейнер
+COPY requirements.txt /workspace/requirements.txt
+
+# Установка зависимостей Python из файла требований
+RUN pip install --no-cache-dir -r /workspace/requirements.txt
+
+# Копирование оставшегося исходного кода проекта в контейнер
+COPY . /workspace
+
+# Установка рабочей директории
+WORKDIR /workspace
+
+# Команда по умолчанию, запускающая оболочку bash
+CMD ["bash"]

PSGUI.py

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+import sys
+from PyQt5 import QtWidgets, QtGui
+from PyQt5.QtWidgets import (
+    QFileDialog,
+    QLabel,
+    QVBoxLayout,
+    QHBoxLayout,
+    QPushButton,
+    QSlider,
+    QWidget,
+    QApplication,
+)
+from PyQt5.QtCore import Qt
+from PIL import Image, ImageDraw, ImageFont
+import zipfile
+from pathlib import Path
+import pandas as pd
+from tqdm import tqdm
+from detect_function_dual import detect_image_dual
+from detect_function import detect_image
+
+# Переключатель для выбора функции детекции
+use_dual_function = (
+    True  # Установите в False для использования стандартной функции детекции
+)
+
+# Путь к весам модели
+weight_path = (
+    r"C:\Users\pasha\OneDrive\Рабочий стол\yolo_weights\yolo_word_detectino21.pt"
+)
+
+
+class MainApp(QWidget):
+    def __init__(self):
+        super().__init__()
+
+        self.initUI()
+
+    def initUI(self):
+        self.setWindowTitle("YOLO Detection")
+        self.setGeometry(100, 100, 800, 600)
+
+        layout = QVBoxLayout()
+
+        self.imageLabel = QLabel(self)
+        self.imageLabel.setAlignment(Qt.AlignCenter)
+        layout.addWidget(self.imageLabel)
+
+        self.loadButton = QPushButton("Load Image or Zip", self)
+        self.loadButton.clicked.connect(self.loadFile)
+        layout.addWidget(self.loadButton)
+
+        self.confSlider = QSlider(Qt.Horizontal)
+        self.confSlider.setRange(0, 100)
+        self.confSlider.setValue(25)
+        self.confSlider.setTickInterval(5)
+        self.confSlider.setTickPosition(QSlider.TicksBelow)
+        layout.addWidget(QLabel("Confidence Threshold"))
+        layout.addWidget(self.confSlider)
+
+        self.iouSlider = QSlider(Qt.Horizontal)
+        self.iouSlider.setRange(0, 100)
+        self.iouSlider.setValue(45)
+        self.iouSlider.setTickInterval(5)
+        self.iouSlider.setTickPosition(QSlider.TicksBelow)
+        layout.addWidget(QLabel("IoU Threshold"))
+        layout.addWidget(self.iouSlider)
+
+        self.processButton = QPushButton("Process", self)
+        self.processButton.clicked.connect(self.processFile)
+        layout.addWidget(self.processButton)
+
+        self.setLayout(layout)
+
+    def draw_boxes(self, image, results):
+        draw = ImageDraw.Draw(image)
+        font = ImageFont.load_default()
+        for result in results:
+            x1, y1, x2, y2 = result["bbox"]
+            confidence = result["conf"]
+            class_id = result["cls"]
+            draw.rectangle([x1, y1, x2, y2], outline="red", width=2)
+            text = f"Class {int(class_id)} {confidence:.2f}"
+            text_size = draw.textbbox((0, 0), text, font=font)
+            text_location = [x1, y1 - text_size[3]]
+            if text_location[1] < 0:
+                text_location[1] = y1 + text_size[3]
+            draw.rectangle([x1, y1 - text_size[3], x1 + text_size[2], y1], fill="red")
+            draw.text((x1, y1 - text_size[3]), text, fill="white", font=font)
+        return image
+
+    def loadFile(self):
+        options = QFileDialog.Options()
+        fileName, _ = QFileDialog.getOpenFileName(
+            self,
+            "Open Image or Zip",
+            "",
+            "Images (*.png *.xpm *.jpg);;Zip Files (*.zip)",
+            options=options,
+        )
+        if fileName:
+            self.filePath = fileName
+            self.imageLabel.setPixmap(QtGui.QPixmap(fileName))
+
+    def processFile(self):
+        if not hasattr(self, "filePath"):
+            QtWidgets.QMessageBox.warning(self, "Error", "No file loaded")
+            return
+
+        conf_thres = self.confSlider.value() / 100
+        iou_thres = self.iouSlider.value() / 100
+        file_path = Path(self.filePath)
+        detection_function = detect_image_dual if use_dual_function else detect_image
+
+        if file_path.suffix in [".jpg", ".jpeg", ".png"]:
+            try:
+                results = detection_function(
+                    weight_path,
+                    file_path,
+                    device="cpu",
+                    conf_thres=conf_thres,
+                    iou_thres=iou_thres,
+                )
+                image = Image.open(file_path)
+                detected_image = self.draw_boxes(image, results)
+                detected_image.save("output.jpg")
+                self.imageLabel.setPixmap(QtGui.QPixmap("output.jpg"))
+            except Exception as e:
+                QtWidgets.QMessageBox.critical(
+                    self, "Error", f"Error processing image: {str(e)}"
+                )
+        elif file_path.suffix in [".zip"]:
+            try:
+                with zipfile.ZipFile(file_path, "r") as zip_ref:
+                    zip_ref.extractall("temp_images")
+                detected_results = []
+                csv_data = []
+                image_files = list(Path("temp_images").glob("*"))
+                for img_path in tqdm(image_files, desc="Processing Images"):
+                    if img_path.suffix in [".jpg", ".jpeg", ".png"]:
+                        try:
+                            results = detection_function(
+                                weight_path,
+                                img_path,
+                                device="cpu",
+                                conf_thres=conf_thres,
+                                iou_thres=iou_thres,
+                            )
+                            image = Image.open(img_path)
+                            detected_image = self.draw_boxes(image, results)
+                            detected_results.append(detected_image)
+                            for result in results:
+                                box = result["bbox"]
+                                confidence = result["conf"]
+                                class_id = result["cls"]
+                                csv_data.append(
+                                    [img_path.name, int(class_id), confidence, *box]
+                                )
+                        except Exception as e:
+                            print(f"Error processing image {img_path}: {str(e)}")
+
+                csv_df = pd.DataFrame(
+                    csv_data,
+                    columns=["Filename", "Class", "Confidence", "X1", "Y1", "X2", "Y2"],
+                )
+                save_path, _ = QFileDialog.getSaveFileName(
+                    self, "Save CSV", "", "CSV Files (*.csv)"
+                )
+                if save_path:
+                    csv_df.to_csv(save_path, index=False)
+                else:
+                    QtWidgets.QMessageBox.information(
+                        self, "Cancelled", "CSV save cancelled"
+                    )
+            except Exception as e:
+                QtWidgets.QMessageBox.critical(
+                    self, "Error", f"Error processing archive: {str(e)}"
+                )
+        else:
+            QtWidgets.QMessageBox.warning(self, "Error", "Unsupported file format")
+
+
+if __name__ == "__main__":
+    app = QApplication(sys.argv)
+    mainApp = MainApp()
+    mainApp.show()
+    sys.exit(app.exec_())