完善相关问题，并增加推理的部分代码

app/service/project_detect_service.py

@@ -0,0 +1,132 @@
+from sqlalchemy.orm import Session
+from typing import List
+from fastapi import UploadFile
+import subprocess
+
+from app.model.crud import project_detect_crud as pdc
+from app.model.schemas.project_detect_schemas import ProjectDetectIn, ProjectDetectOut, ProjectDetectLogIn
+from app.model.bussiness_model import ProjectDetect, ProjectDetectImg, ProjectTrain, ProjectDetectLog
+from app.util.random_utils import random_str
+from app.config.config_reader import detect_url
+from app.util import os_utils as os
+from app.util import random_utils as ru
+from app.config.config_reader import yolo_url
+
+
+def add_detect(detect_in: ProjectDetectIn, session: Session):
+    """
+    新增训练集合信息,并创建文件夹
+    :param detect_in:
+    :param session:
+    :return:
+    """
+    detect = ProjectDetect(**detect_in.dict())
+    detect.detect_no = random_str(6)
+    detect.detect_version = 0
+    url = os.create_folder(detect_url, detect.detect_no, 'images')
+    detect.folder_url = url
+    detect = pdc.add_detect(detect, session)
+    return detect
+
+
+def check_image_name(detect_id: int, files: List[UploadFile], session: Session):
+    """
+    校验上传的文件名称是否重复
+    :param detect_id:
+    :param files:
+    :param session:
+    :return:
+    """
+    for file in files:
+        if not pdc.check_img_name(detect_id, file.filename, session):
+            return False, file.filename
+    return True, None
+
+
+def upload_detect_imgs(detect: ProjectDetectOut, files: List[UploadFile], session: Session):
+    """
+    上传推理集合的照片，保存原图，并生成缩略图
+    :param detect:
+    :param files:
+    :param session:
+    :return:
+    """
+    images = []
+    for file in files:
+        image = ProjectDetectImg()
+        image.detect_id = detect.id
+        image.file_name = file.filename
+        # 保存原图
+        path = os.save_images(detect.folder_url, file=file)
+        image.image_url = path
+        # 生成缩略图
+        thumb_image_url = os.file_path(detect.folder_url, 'thumb', ru.random_str(10) + ".jpg")
+        os.create_thumbnail(path, thumb_image_url)
+        image.thumb_image_url = thumb_image_url
+        images.append(image)
+    pdc.add_detect_imgs(images, session)
+
+
+def run_detect_yolo(detect_in: ProjectDetectLogIn, detect: ProjectDetect, train: ProjectTrain, session: Session):
+    """
+    开始推理
+    :param detect:
+    :param detect_in:
+    :param train:
+    :param session:
+    :return:
+    """
+    # 推理版本
+    version_path = 'v' + str(detect.detect_version + 1)
+
+    # 权重文件
+    pt_url = train.best_pt if detect_in.pt_type == 'best' else train.last_pt
+
+    # 推理集合文件路径
+    img_url = detect.folder_url
+
+    out_url = os.file_path(detect_url, detect.detect_no, 'detect')
+
+    # 构建推理记录数据
+    detect_log = ProjectDetectLog()
+    detect_log.detect_id = detect.id
+    detect_log.detect_version = version_path
+    detect_log.train_id = train.id
+    detect_log.train_version = train.train_version
+    detect_log.pt_type = detect_in.pt_type
+    detect_log.folder_url = detect.folder_url
+    detect_log.detect_folder_url = out_url
+    detect_log = pdc.add_detect_log(detect_log, session)
+    return detect_log
+
+
+def run_commend(weights: str, source: str, project: str, name: str,
+                detect_log_id: int, session: Session):
+    yolo_path = os.file_path(yolo_url, 'detect.py')
+
+    yield f"stdout: 模型推理开始，请稍等。。。 \n"
+    # 启动子进程
+    with subprocess.Popen(
+            ["python", '-u', yolo_path,
+             "--weights =" + weights,
+             "--source =" + source,
+             "--name=" + name,
+             "--project=" + project,
+             "--view-img"],
+            bufsize=1,  # bufsize=0时，为不缓存；bufsize=1时，按行缓存；bufsize为其他正整数时，为按照近似该正整数的字节数缓存
+            shell=False,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.STDOUT,  # 这里可以显示yolov5训练过程中出现的进度条等信息
+            text=True,  # 缓存内容为文本，避免后续编码显示问题
+            encoding='utf-8',
+    ) as process:
+        while process.poll() is None:
+            line = process.stdout.readline()
+            process.stdout.flush()  # 刷新缓存，防止缓存过多造成卡死
+            if line != '\n':
+                yield line
+
+
+
+
+

app/service/project_train_service.py

@@ -67,6 +67,22 @@ def upload_project_image(project_info: ProjectInfoOut, files: List[UploadFile],
     pimc.add_image_batch(images, session)
 
 
+def del_img(image_id: int, session: Session):
+    """
+    删除图片，并删除文件
+    :param image_id:
+    :param session:
+    :return:
+    """
+    image = session.query(ProjectImage).filter_by(id=image_id).first()
+    if image is None:
+        return 0
+    os.delete_file_if_exists(image.image_url, image.thumb_image_url)
+    session.delete(image)
+    session.commit()
+
+
+
 def save_img_label(img_leafer_label: ProjectImgLeaferLabel, session: Session):
     """
     保存图片的标签框选信息，每次保存都会针对图片的信息全部删除，然后重新保存
@@ -164,7 +180,8 @@ def run_commend(data: str, project: str,
                 name: str, epochs: int,
                 project_id: int, session: Session):
     yolo_path = os.file_path(yolo_url, 'train.py')
-    yield f"stdout: 模型训练开始，请稍等。。。"
+
+    yield f"stdout: 模型训练开始，请稍等。。。\n"
     # 启动子进程
     with subprocess.Popen(
             ["python", '-u', yolo_path,
@@ -195,8 +212,8 @@ def run_commend(data: str, project: str,
             train = ProjectTrain()
             train.project_id = project_id
             train.train_version = name
-            bast_pt_path = os.file_path(project, name, 'weight', 'bast.pt')
-            last_pt_path = os.file_path(project, name, 'weight', 'last.pt')
+            bast_pt_path = os.file_path(project, name, 'weights', 'bast.pt')
+            last_pt_path = os.file_path(project, name, 'weights', 'last.pt')
             train.best_pt = bast_pt_path
             train.last_pt = last_pt_path
             ptc.add_train(train, session)