20260430_001744-feat: PyTorch CUDA + SAM2 GPU inference, video thumbnail, real FPS + configurable parse FPS, DICOM batch import

.vscode/settings.json

@@ -0,0 +1,5 @@
+{
+    "workbench.editorAssociations": {
+        "*.mp4": "default"
+    }
+}

backend/config.py

@@ -20,7 +20,7 @@ class Settings(BaseSettings):
 
     # SAM2
     sam_model_path: str = "/home/wkmgc/Desktop/Seg_Server/models/sam2_hiera_tiny.pt"
-    sam_model_config: str = "sam2_hiera_t.yaml"
+    sam_model_config: str = "configs/sam2/sam2_hiera_t.yaml"
 
     # App
     app_env: str = "development"

backend/main.py

@@ -30,7 +30,7 @@ def _seed_default_project_sync() -> None:
     """Synchronously seed the default video project on first startup."""
     import cv2
     from models import Project, Frame
-    from services.frame_parser import parse_video, upload_frames_to_minio
+    from services.frame_parser import parse_video, upload_frames_to_minio, extract_thumbnail
 
     db = SessionLocal()
     try:
@@ -46,6 +46,8 @@ def _seed_default_project_sync() -> None:
             name="Data_MyVideo_1",
             description="默认演示视频",
             status="pending",
+            source_type="video",
+            parse_fps=30.0,
         )
         db.add(project)
         db.commit()
@@ -67,7 +69,20 @@ def _seed_default_project_sync() -> None:
                 f.write(data)
             output_dir = os.path.join(tmp_dir, "frames")
             os.makedirs(output_dir, exist_ok=True)
-            frame_files = parse_video(local_path, output_dir, fps=30, max_frames=100)
+            frame_files, original_fps = parse_video(local_path, output_dir, fps=30, max_frames=100)
+            project.original_fps = original_fps
+
+            # Extract thumbnail
+            thumbnail_path = os.path.join(tmp_dir, "thumbnail.jpg")
+            try:
+                extract_thumbnail(local_path, thumbnail_path)
+                with open(thumbnail_path, "rb") as f:
+                    thumb_data = f.read()
+                thumb_object = f"projects/{project.id}/thumbnail.jpg"
+                upload_file(thumb_object, thumb_data, content_type="image/jpeg", length=len(thumb_data))
+                project.thumbnail_url = thumb_object
+            except Exception as exc:  # noqa: BLE001
+                logger.warning("Thumbnail extraction failed: %s", exc)
 
             object_names = upload_frames_to_minio(frame_files, project.id)
 

backend/models.py

@@ -25,7 +25,11 @@ class Project(Base):
     name = Column(String(255), nullable=False)
     description = Column(Text, nullable=True)
     video_path = Column(String(512), nullable=True)
+    thumbnail_url = Column(String(512), nullable=True)
     status = Column(String(50), default="Ready", nullable=False)
+    source_type = Column(String(20), default="video", nullable=False)  # video | dicom
+    original_fps = Column(Float, nullable=True)
+    parse_fps = Column(Float, default=30.0, nullable=False)
     created_at = Column(DateTime(timezone=True), server_default=func.now())
     updated_at = Column(
         DateTime(timezone=True), server_default=func.now(), onupdate=func.now()

backend/routers/media.py

@@ -6,16 +6,19 @@ import shutil
 import subprocess
 import tempfile
 from pathlib import Path
-from typing import Optional
+from typing import List, Optional
 
 from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile, status
 from sqlalchemy.orm import Session
 
 from database import get_db
-from minio_client import upload_file, get_presigned_url
+from minio_client import upload_file, get_presigned_url, download_file
 from models import Project, Frame
 from schemas import FrameOut
-from services.frame_parser import parse_video, parse_dicom, upload_frames_to_minio
+from services.frame_parser import (
+    parse_video, parse_dicom, upload_frames_to_minio,
+    extract_thumbnail, get_video_fps,
+)
 
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/api/media", tags=["Media"])
@@ -78,6 +81,7 @@ async def upload_media(
             description="Auto-created from upload",
             status="pending",
             video_path=object_name,
+            source_type="video",
         )
         db.add(project)
         db.commit()
@@ -90,7 +94,6 @@ async def upload_media(
         db.commit()
         logger.info("Auto-created project id=%s for upload %s", project_id, file.filename)
 
-    # TODO: enqueue async parsing job (Celery / background task)
     logger.info("Upload complete: %s (size=%d bytes). Async parsing queued.", object_name, len(data))
 
     return {
@@ -102,6 +105,66 @@ async def upload_media(
     }
 
 
+@router.post(
+    "/upload/dicom",
+    status_code=status.HTTP_201_CREATED,
+    summary="Upload multiple DICOM files",
+)
+async def upload_dicom_batch(
+    files: List[UploadFile] = File(...),
+    project_id: Optional[int] = Form(None),
+    db: Session = Depends(get_db),
+) -> dict:
+    """Upload multiple .dcm files for a DICOM series.
+
+    If project_id is provided, files are added to the existing project.
+    Otherwise a new DICOM project is created.
+    """
+    if not files:
+        raise HTTPException(status_code=400, detail="No files uploaded")
+
+    uploaded = []
+
+    if project_id:
+        project = db.query(Project).filter(Project.id == project_id).first()
+        if not project:
+            raise HTTPException(status_code=404, detail="Project not found")
+    else:
+        # Create new DICOM project
+        first_name = files[0].filename or "DICOM_Series"
+        project = Project(
+            name=first_name,
+            description=f"DICOM series with {len(files)} files",
+            status="pending",
+            source_type="dicom",
+        )
+        db.add(project)
+        db.commit()
+        db.refresh(project)
+        project_id = project.id
+        logger.info("Auto-created DICOM project id=%s", project_id)
+
+    for file in files:
+        if not file.filename or not file.filename.lower().endswith(".dcm"):
+            continue
+        data = await file.read()
+        object_name = f"uploads/{project_id}/dicom/{file.filename}"
+        try:
+            upload_file(object_name, data, content_type="application/dicom", length=len(data))
+            uploaded.append(object_name)
+        except Exception as exc:  # noqa: BLE001
+            logger.error("Failed to upload DICOM %s: %s", file.filename, exc)
+
+    project.video_path = f"uploads/{project_id}/dicom"
+    db.commit()
+
+    return {
+        "project_id": project_id,
+        "uploaded_count": len(uploaded),
+        "message": f"Uploaded {len(uploaded)} DICOM files. Parsing job queued.",
+    }
+
+
 @router.post(
     "/parse",
     status_code=status.HTTP_202_ACCEPTED,
@@ -109,12 +172,12 @@ async def upload_media(
 )
 def parse_media(
     project_id: int,
-    source_type: str = "video",  # video | dicom
+    source_type: Optional[str] = None,
     db: Session = Depends(get_db),
 ) -> dict:
     """Trigger frame extraction for a project's uploaded media.
 
-    * video: uses FFmpeg or OpenCV fallback.
+    * video: uses FFmpeg or OpenCV fallback, extracts thumbnail.
     * dicom: uses pydicom to read DCM frames.
 
     Extracted frames are uploaded to MinIO and registered in the database.
@@ -126,37 +189,53 @@ def parse_media(
     if not project.video_path:
         raise HTTPException(status_code=400, detail="Project has no media uploaded")
 
-    # Download from MinIO to a temp directory
-    from minio_client import download_file
-
-    try:
-        media_bytes = download_file(project.video_path)
-    except Exception as exc:  # noqa: BLE001
-        logger.error("Failed to download media for parsing: %s", exc)
-        raise HTTPException(status_code=500, detail="Failed to retrieve media from storage") from exc
+    effective_source = source_type or project.source_type or "video"
+    parse_fps = project.parse_fps or 30.0
 
     tmp_dir = tempfile.mkdtemp(prefix=f"seg_parse_{project_id}_")
-    local_path = os.path.join(tmp_dir, Path(project.video_path).name)
-
-    with open(local_path, "wb") as f:
-        f.write(media_bytes)
-
     output_dir = os.path.join(tmp_dir, "frames")
     os.makedirs(output_dir, exist_ok=True)
 
     try:
-        if source_type == "dicom":
-            # For DICOM, treat local_path as a directory if it contains multiple .dcm
-            # If a single .dcm file was uploaded, put it in its own sub-dir
+        if effective_source == "dicom":
+            # Download all dicom files from MinIO
             dcm_dir = os.path.join(tmp_dir, "dcm")
             os.makedirs(dcm_dir, exist_ok=True)
-            if local_path.lower().endswith(".dcm"):
-                shutil.move(local_path, os.path.join(dcm_dir, os.path.basename(local_path)))
-            else:
-                shutil.unpack_archive(local_path, dcm_dir) if shutil.which("unzip") else shutil.move(local_path, dcm_dir)
+
+            from minio_client import get_minio_client, BUCKET_NAME
+            client = get_minio_client()
+            prefix = project.video_path
+            objects = list(client.list_objects(BUCKET_NAME, prefix=prefix, recursive=True))
+            for obj in objects:
+                if obj.object_name.lower().endswith(".dcm"):
+                    data = download_file(obj.object_name)
+                    local_dcm = os.path.join(dcm_dir, os.path.basename(obj.object_name))
+                    with open(local_dcm, "wb") as f:
+                        f.write(data)
+
             frame_files = parse_dicom(dcm_dir, output_dir)
         else:
-            frame_files = parse_video(local_path, output_dir, fps=30)
+            # Video: download and parse
+            media_bytes = download_file(project.video_path)
+            local_path = os.path.join(tmp_dir, Path(project.video_path).name)
+            with open(local_path, "wb") as f:
+                f.write(media_bytes)
+
+            frame_files, original_fps = parse_video(local_path, output_dir, fps=int(parse_fps))
+            project.original_fps = original_fps
+
+            # Extract thumbnail from first frame
+            thumbnail_path = os.path.join(tmp_dir, "thumbnail.jpg")
+            try:
+                extract_thumbnail(local_path, thumbnail_path)
+                with open(thumbnail_path, "rb") as f:
+                    thumb_data = f.read()
+                thumb_object = f"projects/{project_id}/thumbnail.jpg"
+                upload_file(thumb_object, thumb_data, content_type="image/jpeg", length=len(thumb_data))
+                project.thumbnail_url = thumb_object
+                logger.info("Uploaded thumbnail for project_id=%s", project_id)
+            except Exception as exc:  # noqa: BLE001
+                logger.warning("Thumbnail extraction failed: %s", exc)
     except Exception as exc:  # noqa: BLE001
         logger.error("Frame extraction failed: %s", exc)
         shutil.rmtree(tmp_dir, ignore_errors=True)
@@ -173,7 +252,6 @@ def parse_media(
     # Register frames in DB
     frames_out = []
     for idx, obj_name in enumerate(object_names):
-        # Get image dimensions
         local_frame = frame_files[idx]
         try:
             import cv2

backend/routers/projects.py

@@ -44,6 +44,8 @@ def list_projects(skip: int = 0, limit: int = 100, db: Session = Depends(get_db)
     projects = db.query(Project).offset(skip).limit(limit).all()
     for p in projects:
         p.frame_count = len(p.frames)
+        if p.thumbnail_url:
+            p.thumbnail_url = get_presigned_url(p.thumbnail_url, expires=3600)
     return projects
 
 
@@ -58,6 +60,8 @@ def get_project(project_id: int, db: Session = Depends(get_db)) -> Project:
     if not project:
         raise HTTPException(status_code=404, detail="Project not found")
     project.frame_count = len(project.frames)
+    if project.thumbnail_url:
+        project.thumbnail_url = get_presigned_url(project.thumbnail_url, expires=3600)
     return project
 
 

backend/schemas.py

@@ -12,7 +12,11 @@ class ProjectBase(BaseModel):
     name: str
     description: Optional[str] = None
     video_path: Optional[str] = None
+    thumbnail_url: Optional[str] = None
     status: Optional[str] = "pending"
+    source_type: Optional[str] = "video"
+    original_fps: Optional[float] = None
+    parse_fps: Optional[float] = 30.0
 
 
 class ProjectCreate(ProjectBase):
@@ -23,7 +27,11 @@ class ProjectUpdate(BaseModel):
     name: Optional[str] = None
     description: Optional[str] = None
     video_path: Optional[str] = None
+    thumbnail_url: Optional[str] = None
     status: Optional[str] = None
+    source_type: Optional[str] = None
+    original_fps: Optional[float] = None
+    parse_fps: Optional[float] = None
 
 
 class ProjectOut(ProjectBase):
@@ -103,7 +111,7 @@ class AnnotationCreate(AnnotationBase):
 
 class AnnotationUpdate(BaseModel):
     mask_data: Optional[dict[str, Any]] = None
-    points: Optional[list[list[float]]] = None
+    points: Optional[list[float]] = None
     bbox: Optional[list[float]] = None
     template_id: Optional[int] = None
 

backend/services/frame_parser.py

@@ -5,7 +5,7 @@ import os
 import shutil
 import subprocess
 from pathlib import Path
-from typing import List, Optional
+from typing import List, Optional, Tuple
 
 import cv2
 import numpy as np
@@ -16,12 +16,43 @@ from minio_client import upload_file, BUCKET_NAME
 logger = logging.getLogger(__name__)
 
 
+def get_video_fps(video_path: str) -> float:
+    """Read the original frame rate of a video file."""
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        return 30.0
+    fps = cap.get(cv2.CAP_PROP_FPS)
+    cap.release()
+    return fps if fps > 0 else 30.0
+
+
+def extract_thumbnail(video_path: str, output_path: str, width: int = 640) -> str:
+    """Extract the first frame of a video as a thumbnail JPEG."""
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        raise RuntimeError(f"Cannot open video for thumbnail: {video_path}")
+    ret, frame = cap.read()
+    cap.release()
+    if not ret or frame is None:
+        raise RuntimeError(f"Cannot read first frame from: {video_path}")
+
+    h, w = frame.shape[:2]
+    if w > width:
+        scale = width / w
+        new_w = int(w * scale)
+        new_h = int(h * scale)
+        frame = cv2.resize(frame, (new_w, new_h), interpolation=cv2.INTER_AREA)
+
+    cv2.imwrite(output_path, frame, [cv2.IMWRITE_JPEG_QUALITY, 85])
+    return output_path
+
+
 def parse_video(
     video_path: str,
     output_dir: str,
     fps: int = 30,
     max_frames: Optional[int] = None,
-) -> List[str]:
+) -> Tuple[List[str], float]:
     """Extract frames from a video file using FFmpeg or OpenCV fallback.
 
     Args:
@@ -31,10 +62,11 @@ def parse_video(
         max_frames: Optional maximum number of frames to extract.
 
     Returns:
-        List of paths to extracted frame images.
+        Tuple of (frame_paths, original_fps).
     """
     os.makedirs(output_dir, exist_ok=True)
     frame_paths: List[str] = []
+    original_fps = get_video_fps(video_path)
 
     # Try FFmpeg first
     if shutil.which("ffmpeg"):
@@ -57,7 +89,7 @@ def parse_video(
                 if max_frames:
                     frame_paths = frame_paths[:max_frames]
                 logger.info("Extracted %d frames via FFmpeg", len(frame_paths))
-                return frame_paths
+                return frame_paths, original_fps
             else:
                 logger.warning("FFmpeg failed: %s", result.stderr)
         except Exception as exc:  # noqa: BLE001
@@ -89,7 +121,7 @@ def parse_video(
 
     cap.release()
     logger.info("Extracted %d frames via OpenCV", len(frame_paths))
-    return frame_paths
+    return frame_paths, original_fps
 
 
 def parse_dicom(
@@ -134,12 +166,12 @@ def parse_dicom(
             # Handle multi-frame DICOM
             if pixel_array.ndim == 3:
                 for f in range(pixel_array.shape[0]):
-                    out_path = os.path.join(output_dir, f"frame_{idx:06d}_{f:03d}.png")
-                    cv2.imwrite(out_path, pixel_array[f])
+                    out_path = os.path.join(output_dir, f"frame_{idx:06d}_{f:03d}.jpg")
+                    cv2.imwrite(out_path, pixel_array[f], [cv2.IMWRITE_JPEG_QUALITY, 85])
                     frame_paths.append(out_path)
             else:
-                out_path = os.path.join(output_dir, f"frame_{idx:06d}.png")
-                cv2.imwrite(out_path, pixel_array)
+                out_path = os.path.join(output_dir, f"frame_{idx:06d}.jpg")
+                cv2.imwrite(out_path, pixel_array, [cv2.IMWRITE_JPEG_QUALITY, 85])
                 frame_paths.append(out_path)
         except Exception as exc:  # noqa: BLE001
             logger.error("Failed to read DICOM %s: %s", path, exc)

src/components/ProjectLibrary.tsx

@@ -1,8 +1,8 @@
 import React, { useState, useEffect, useRef } from 'react';
-import { UploadCloud, Film, Settings2, MoreHorizontal, Plus, Loader2 } from 'lucide-react';
+import { UploadCloud, Film, Settings2, MoreHorizontal, Plus, Loader2, Activity } from 'lucide-react';
 import { cn } from '../lib/utils';
 import { useStore } from '../store/useStore';
-import { getProjects, createProject, uploadMedia, parseMedia } from '../lib/api';
+import { getProjects, createProject, uploadMedia, parseMedia, uploadDicomBatch } from '../lib/api';
 import type { Project } from '../store/useStore';
 
 interface ProjectLibraryProps {
@@ -19,7 +19,12 @@ export function ProjectLibrary({ onProjectSelect }: ProjectLibraryProps) {
   const [showModal, setShowModal] = useState(false);
   const [newName, setNewName] = useState('');
   const [newDesc, setNewDesc] = useState('');
-  const fileInputRef = useRef<HTMLInputElement>(null);
+  const [showImportMenu, setShowImportMenu] = useState(false);
+  const [showVideoConfig, setShowVideoConfig] = useState(false);
+  const [pendingFile, setPendingFile] = useState<File | null>(null);
+  const [parseFps, setParseFps] = useState(30);
+  const videoInputRef = useRef<HTMLInputElement>(null);
+  const dicomInputRef = useRef<HTMLInputElement>(null);
 
   useEffect(() => {
     setIsLoading(true);
@@ -50,6 +55,60 @@ export function ProjectLibrary({ onProjectSelect }: ProjectLibraryProps) {
     onProjectSelect();
   };
 
+  const handleVideoSelect = (file: File) => {
+    setPendingFile(file);
+    setParseFps(30);
+    setShowVideoConfig(true);
+  };
+
+  const handleVideoUpload = async () => {
+    if (!pendingFile) return;
+    setShowVideoConfig(false);
+    setIsLoading(true);
+    try {
+      const newProject = await createProject({
+        name: pendingFile.name,
+        description: `导入于 ${new Date().toLocaleString()}`,
+        parse_fps: parseFps,
+      });
+      const result = await uploadMedia(pendingFile, String(newProject.id));
+      await parseMedia(String(newProject.id));
+      alert(`上传成功: ${pendingFile.name}\n已保存至: ${result.url}`);
+      const data = await getProjects();
+      setProjects(data);
+    } catch (err) {
+      console.error('Upload failed:', err);
+      alert('上传失败，请检查后端服务');
+    } finally {
+      setIsLoading(false);
+      setPendingFile(null);
+      if (videoInputRef.current) videoInputRef.current.value = '';
+    }
+  };
+
+  const handleDicomUpload = async (files: FileList | null) => {
+    if (!files || files.length === 0) return;
+    const dcmFiles = Array.from(files).filter((f) => f.name.toLowerCase().endsWith('.dcm'));
+    if (dcmFiles.length === 0) {
+      alert('未选择有效的 .dcm 文件');
+      return;
+    }
+    setIsLoading(true);
+    try {
+      const result = await uploadDicomBatch(dcmFiles);
+      await parseMedia(String(result.project_id));
+      alert(`DICOM 上传成功: ${result.uploaded_count} 个文件`);
+      const data = await getProjects();
+      setProjects(data);
+    } catch (err) {
+      console.error('DICOM upload failed:', err);
+      alert('DICOM 上传失败，请检查后端服务');
+    } finally {
+      setIsLoading(false);
+      if (dicomInputRef.current) dicomInputRef.current.value = '';
+    }
+  };
+
   const SkeletonCard = () => (
     <div className="group flex flex-col bg-[#111] border border-white/5 rounded-xl overflow-hidden animate-pulse">
       <div className="w-full aspect-[16/9] bg-[#1a1a1a]" />
@@ -75,45 +134,51 @@ export function ProjectLibrary({ onProjectSelect }: ProjectLibraryProps) {
             <Plus size={18} />
             <span>新建项目</span>
           </button>
-          <button
-            onClick={() => fileInputRef.current?.click()}
-            className="flex items-center gap-2 bg-cyan-600 hover:bg-cyan-500 text-white px-5 py-2.5 rounded-lg font-medium text-sm transition-colors border border-cyan-500 shadow-lg shadow-cyan-900/20"
-          >
-            <UploadCloud size={18} />
-            <span>导入多媒体资源</span>
-          </button>
+          <div className="relative">
+            <button
+              onClick={() => setShowImportMenu(!showImportMenu)}
+              className="flex items-center gap-2 bg-cyan-600 hover:bg-cyan-500 text-white px-5 py-2.5 rounded-lg font-medium text-sm transition-colors border border-cyan-500 shadow-lg shadow-cyan-900/20"
+            >
+              <UploadCloud size={18} />
+              <span>导入多媒体资源</span>
+            </button>
+            {showImportMenu && (
+              <div className="absolute right-0 top-full mt-2 w-56 bg-[#111] border border-white/10 rounded-lg shadow-2xl z-50 overflow-hidden">
+                <button
+                  className="w-full text-left px-4 py-3 text-sm text-gray-200 hover:bg-white/5 flex items-center gap-3 transition-colors"
+                  onClick={() => { setShowImportMenu(false); videoInputRef.current?.click(); }}
+                >
+                  <Film size={16} className="text-cyan-400" />
+                  导入视频文件
+                </button>
+                <button
+                  className="w-full text-left px-4 py-3 text-sm text-gray-200 hover:bg-white/5 flex items-center gap-3 transition-colors border-t border-white/5"
+                  onClick={() => { setShowImportMenu(false); dicomInputRef.current?.click(); }}
+                >
+                  <Activity size={16} className="text-emerald-400" />
+                  导入 DICOM 序列
+                </button>
+              </div>
+            )}
+          </div>
           <input
             type="file"
-            ref={fileInputRef}
+            ref={videoInputRef}
             className="hidden"
-            accept="video/*,image/*,.dcm"
-            onChange={async (e) => {
+            accept="video/*"
+            onChange={(e) => {
               const file = e.target.files?.[0];
-              if (!file) return;
-              try {
-                setIsLoading(true);
-                // 1. 创建项目
-                const newProject = await createProject({
-                  name: file.name,
-                  description: `导入于 ${new Date().toLocaleString()}`,
-                });
-                // 2. 带 project_id 上传
-                const result = await uploadMedia(file, String(newProject.id));
-                // 3. 触发帧解析
-                await parseMedia(String(newProject.id));
-                alert(`上传成功: ${file.name}\n已保存至: ${result.url}`);
-                // 4. 刷新项目列表
-                const data = await getProjects();
-                setProjects(data);
-              } catch (err) {
-                console.error('Upload failed:', err);
-                alert('上传失败，请检查后端服务');
-              } finally {
-                setIsLoading(false);
-                if (fileInputRef.current) fileInputRef.current.value = '';
-              }
+              if (file) handleVideoSelect(file);
             }}
           />
+          <input
+            type="file"
+            ref={dicomInputRef}
+            className="hidden"
+            accept=".dcm"
+            multiple
+            onChange={(e) => handleDicomUpload(e.target.files)}
+          />
         </div>
       </div>
 
@@ -126,29 +191,38 @@ export function ProjectLibrary({ onProjectSelect }: ProjectLibraryProps) {
       ) : (
         <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 xl:grid-cols-4 gap-6">
           {projects.map((proj) => (
-            <div 
-              key={proj.id} 
+            <div
+              key={proj.id}
               className="group flex flex-col bg-[#111] border border-white/5 rounded-xl overflow-hidden cursor-pointer hover:border-cyan-500/50 transition-all hover:shadow-[0_0_20px_rgba(6,182,212,0.15)]"
               onClick={() => handleSelect(proj)}
             >
-              <div className={cn("w-full aspect-[16/9] relative flex items-center justify-center overflow-hidden", proj.thumbnail || 'bg-[#0d0d0d]')}>
-                 <Film className="w-12 h-12 text-[#2a2a2a] group-hover:text-[#333] transition-colors" />
-                 <div className="absolute top-2 right-2 flex gap-2">
-                   <span className="backdrop-blur-md bg-black/40 text-gray-200 text-[10px] font-mono px-2 py-1 rounded border border-white/10 uppercase tracking-widest">
-                     {proj.fps || '30FPS'}
-                   </span>
-                   <span className="backdrop-blur-md bg-black/40 text-gray-200 text-[10px] px-2 py-1 rounded border border-white/10 flex items-center gap-1 uppercase tracking-widest">
-                     {proj.status === 'Ready' || proj.status === 'ready' ? (
-                       <><div className="w-1.5 h-1.5 bg-emerald-500 rounded-full" /> 已就绪</>
-                     ) : proj.status === 'Parsing' || proj.status === 'parsing' ? (
-                       <><div className="w-1.5 h-1.5 bg-amber-500 rounded-full animate-pulse" /> 解析拆帧中</>
-                     ) : proj.status === 'pending' || proj.status === 'Pending' ? (
-                       <><div className="w-1.5 h-1.5 bg-blue-500 rounded-full" /> 待处理</>
-                     ) : (
-                       <><div className="w-1.5 h-1.5 bg-red-500 rounded-full" /> 异常</>
-                     )}
-                   </span>
-                 </div>
+              <div className={cn("w-full aspect-[16/9] relative flex items-center justify-center overflow-hidden bg-[#0d0d0d]")}>
+                {proj.thumbnail_url ? (
+                  <img
+                    src={proj.thumbnail_url}
+                    alt={proj.name}
+                    className="absolute inset-0 w-full h-full object-cover group-hover:scale-105 transition-transform duration-500"
+                    loading="lazy"
+                  />
+                ) : (
+                  <Film className="w-12 h-12 text-[#2a2a2a] group-hover:text-[#333] transition-colors" />
+                )}
+                <div className="absolute top-2 right-2 flex gap-2">
+                  <span className="backdrop-blur-md bg-black/40 text-gray-200 text-[10px] font-mono px-2 py-1 rounded border border-white/10 uppercase tracking-widest">
+                    {proj.source_type === 'dicom' ? 'DICOM' : (proj.fps || '30FPS')}
+                  </span>
+                  <span className="backdrop-blur-md bg-black/40 text-gray-200 text-[10px] px-2 py-1 rounded border border-white/10 flex items-center gap-1 uppercase tracking-widest">
+                    {proj.status === 'Ready' || proj.status === 'ready' ? (
+                      <><div className="w-1.5 h-1.5 bg-emerald-500 rounded-full" /> 已就绪</>
+                    ) : proj.status === 'Parsing' || proj.status === 'parsing' ? (
+                      <><div className="w-1.5 h-1.5 bg-amber-500 rounded-full animate-pulse" /> 解析拆帧中</>
+                    ) : proj.status === 'pending' || proj.status === 'Pending' ? (
+                      <><div className="w-1.5 h-1.5 bg-blue-500 rounded-full" /> 待处理</>
+                    ) : (
+                      <><div className="w-1.5 h-1.5 bg-red-500 rounded-full" /> 异常</>
+                    )}
+                  </span>
+                </div>
               </div>
               <div className="p-4 flex flex-col gap-1">
                 <div className="flex justify-between items-start">
@@ -157,6 +231,9 @@ export function ProjectLibrary({ onProjectSelect }: ProjectLibraryProps) {
                 </div>
                 <div className="flex items-center gap-4 text-xs text-gray-500 font-mono mt-2">
                    <span className="flex items-center gap-1.5"><Settings2 size={12} /> {proj.frames ?? 0} 帧节点</span>
+                   {proj.original_fps && (
+                     <span className="flex items-center gap-1.5 text-cyan-400/80"><Activity size={12} /> 原 {proj.original_fps.toFixed(1)}fps</span>
+                   )}
                 </div>
               </div>
             </div>
@@ -164,6 +241,48 @@ export function ProjectLibrary({ onProjectSelect }: ProjectLibraryProps) {
         </div>
       )}
 
+      {/* Video parse FPS config modal */}
+      {showVideoConfig && pendingFile && (
+        <div className="fixed inset-0 z-50 flex items-center justify-center bg-black/60 backdrop-blur-sm">
+          <div className="bg-[#111] border border-white/10 rounded-2xl p-6 w-full max-w-md shadow-2xl">
+            <h2 className="text-lg font-semibold text-white mb-4">导入视频配置</h2>
+            <div className="space-y-4">
+              <div className="text-sm text-gray-400">文件: <span className="text-gray-200">{pendingFile.name}</span></div>
+              <div>
+                <label className="block text-xs font-medium text-gray-400 uppercase tracking-widest mb-2">解析帧率 (FPS)</label>
+                <div className="flex items-center gap-3">
+                  <input
+                    type="range"
+                    min="1"
+                    max="60"
+                    value={parseFps}
+                    onChange={(e) => setParseFps(parseInt(e.target.value))}
+                    className="flex-1 accent-cyan-500"
+                  />
+                  <span className="text-sm font-mono text-cyan-400 w-12 text-right">{parseFps}</span>
+                </div>
+                <p className="text-[10px] text-gray-600 mt-1">帧率越低，提取的帧越少，处理速度越快</p>
+              </div>
+            </div>
+            <div className="flex justify-end gap-3 mt-6">
+              <button
+                onClick={() => { setShowVideoConfig(false); setPendingFile(null); }}
+                className="px-4 py-2 rounded-lg text-sm text-gray-400 hover:text-white transition-colors"
+              >
+                取消
+              </button>
+              <button
+                onClick={handleVideoUpload}
+                className="px-4 py-2 rounded-lg text-sm font-medium bg-cyan-500 hover:bg-cyan-400 text-black transition-all"
+              >
+                开始导入
+              </button>
+            </div>
+          </div>
+        </div>
+      )}
+
+      {/* New project modal */}
       {showModal && (
         <div className="fixed inset-0 z-50 flex items-center justify-center bg-black/60 backdrop-blur-sm">
           <div className="bg-[#111] border border-white/10 rounded-2xl p-6 w-full max-w-md shadow-2xl">

src/lib/api.ts

@@ -48,10 +48,14 @@ export async function getProjects(): Promise<Project[]> {
     description: p.description,
     status: p.status,
     frames: p.frame_count ?? 0,
-    fps: '30FPS',
+    fps: p.original_fps ? `${Math.round(p.original_fps)}FPS` : '30FPS',
+    thumbnail_url: p.thumbnail_url,
+    video_path: p.video_path,
+    source_type: p.source_type,
+    original_fps: p.original_fps,
+    parse_fps: p.parse_fps,
     createdAt: p.created_at,
     updatedAt: p.updated_at,
-    video_path: p.video_path,
   }));
 }
 
@@ -67,10 +71,14 @@ export async function createProject(payload: {
     description: p.description,
     status: p.status,
     frames: p.frame_count ?? 0,
-    fps: '30FPS',
+    fps: p.original_fps ? `${Math.round(p.original_fps)}FPS` : '30FPS',
+    thumbnail_url: p.thumbnail_url,
+    video_path: p.video_path,
+    source_type: p.source_type,
+    original_fps: p.original_fps,
+    parse_fps: p.parse_fps,
     createdAt: p.created_at,
     updatedAt: p.updated_at,
-    video_path: p.video_path,
   };
 }
 
@@ -135,6 +143,16 @@ export async function getProjectFrames(projectId: string): Promise<Array<{
   return response.data;
 }
 
+export async function uploadDicomBatch(files: File[], projectId?: string): Promise<{ project_id: number; uploaded_count: number; message: string }> {
+  const formData = new FormData();
+  files.forEach((file) => formData.append('files', file));
+  if (projectId) formData.append('project_id', projectId);
+  const response = await apiClient.post('/api/media/upload/dicom', formData, {
+    headers: { 'Content-Type': 'multipart/form-data' },
+  });
+  return response.data;
+}
+
 export async function parseMedia(projectId: string): Promise<{
   project_id: number;
   frames_extracted: number;

src/store/useStore.ts

@@ -8,7 +8,11 @@ export interface Project {
   fps?: string;
   frames?: number;
   thumbnail?: string;
+  thumbnail_url?: string;
   video_path?: string;
+  source_type?: string;
+  original_fps?: number;
+  parse_fps?: number;
   createdAt?: string;
   updatedAt?: string;
 }

工程分析/实现方案-20260430_001744.md

@@ -0,0 +1,62 @@
+# 实现方案 — 2026-04-30
+
+## R1 — PyTorch CUDA + SAM2 安装
+
+### 步骤
+1. `pip uninstall torch torchvision torchaudio -y`
+2. `pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124`
+3. `pip install sam2`
+4. 验证: `torch.cuda.is_available()` → True
+5. 修改 `backend/services/sam2_engine.py`，移除 stub fallback，使用真实 SAM2
+
+### SAM2 模型配置
+- 模型文件: `/home/wkmgc/Desktop/Seg_Server/models/sam2_hiera_tiny.pt` (149MB)
+- 配置文件: 需下载对应 YAML 或使用默认配置
+
+## R2 — 视频封面
+
+### 后端
+1. `frame_parser.py`: `parse_video()` 提取第一帧为 `thumbnail.jpg`
+2. `upload_frames_to_minio()`: 同时上传 thumbnail 到 `projects/{id}/thumbnail.jpg`
+3. `models.py`: Project 增加 `thumbnail_url` 字段
+4. `schemas.py`: ProjectOut 增加 `thumbnail_url`
+5. `projects.py`: list_projects / get_project 返回 thumbnail presigned URL
+
+### 前端
+1. `ProjectLibrary.tsx`: 卡片背景显示 `proj.thumbnail_url` 的 `<img>`
+
+## R3 — 帧率
+
+### 后端
+1. `models.py`: Project 增加 `original_fps` (float), `parse_fps` (float, default=30)
+2. `schemas.py`: ProjectOut / ProjectCreate 增加字段
+3. `frame_parser.py`: 
+   - `parse_video()` 开头用 FFmpeg/FFprobe 读取原始帧率，返回给调用方
+   - 解析时按 `parse_fps` 参数提取帧
+4. `media.py`: `parse_media()` 传入 parse_fps
+5. `main.py`: 默认视频种子逻辑设置 original_fps
+
+### 前端
+1. `useStore.ts`: Project 增加 `original_fps`, `parse_fps`
+2. `api.ts`: getProjects / createProject 映射字段
+3. `ProjectLibrary.tsx`: 显示真实帧率 `original_fps`
+4. 上传时弹窗允许设置 parse_fps
+
+## R4 — DICOM 批量导入
+
+### 后端
+1. `models.py`: Project 增加 `source_type` (str, default="video")
+2. `schemas.py`: ProjectOut 增加 source_type
+3. `media.py`:
+   - `upload_media()` 支持批量上传（`List[UploadFile]`）
+   - 新增 `/api/media/upload/dicom` 接口，专用于批量 .dcm 上传
+   - DICOM 文件存储到 `uploads/{project_id}/dicom/`
+   - 上传完成后可直接触发解析
+4. `frame_parser.py`: `parse_dicom()` 支持从 MinIO 读取整个 dicom 目录
+
+### 前端
+1. `ProjectLibrary.tsx`: 
+   - 导入按钮支持两种模式: 视频导入 / DICOM 序列导入
+   - DICOM 模式: `<input multiple accept=".dcm">`
+   - 上传进度显示
+2. `useStore.ts`: Project 增加 `source_type`

工程分析/测试方案-20260430_001744.md

@@ -0,0 +1,22 @@
+# 测试方案 — 2026-04-30
+
+## TC1 — PyTorch CUDA + SAM2
+1. 后端启动后日志应显示 "SAM2 loaded successfully" 而非 "SAM2 import failed"
+2. `python -c "import torch; print(torch.cuda.is_available())"` → True
+3. `python -c "import sam2; print('OK')"` → OK
+4. 调用 `/api/ai/predict` 应返回真实 polygon，而非 dummy rectangle
+
+## TC2 — 视频封面
+1. 解析视频后，检查 MinIO 中是否存在 `projects/{id}/thumbnail.jpg`
+2. 项目库卡片应显示视频第一帧作为封面背景
+
+## TC3 — 帧率
+1. 上传 25fps 视频，original_fps 应显示 25.0
+2. 设置 parse_fps=10，解析后帧数应为 original_fps 的约 1/3
+3. 项目库显示原始帧率
+
+## TC4 — DICOM 批量导入
+1. 选择 10 个 .dcm 文件批量上传
+2. 项目创建成功，source_type="dicom"
+3. 解析完成后帧数等于上传的 .dcm 数量
+4. 再次向同一项目上传 5 个 .dcm，帧数增加 5

工程分析/经验记录.md

@@ -5,6 +5,50 @@
 
 ---
 
+## 2026-04-30-00-17-44 — PyTorch CUDA + SAM2 + 封面 + 帧率 + DICOM 批量导入
+
+### A. 具体问题
+1. PyTorch 为 CPU 版本，SAM2 未安装，GPU 推理不可用
+2. 项目库视频卡片无封面缩略图
+3. 项目库 FPS 为硬编码 "30FPS"，不显示真实原始帧率，也无法修改解析帧率
+4. 不支持 DICOM 连续帧批量导入
+
+### B. 产生原因
+1. 系统磁盘仅 24GB，PyTorch CUDA wheel (~1GB) + SAM2 编译依赖导致 `No space left on device`
+2. 解析视频时未提取封面，Project 模型无 thumbnail_url 字段
+3. 解析视频时未读取原始帧率，Project 模型无 original_fps / parse_fps 字段
+4. upload 接口仅支持单文件，无批量 DICOM 上传接口，Project 无 source_type 区分视频/DICOM
+
+### C. 解决方案
+1. **磁盘扩容后安装 PyTorch CUDA + SAM2**：
+   - `pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124`
+   - `pip install sam2`（成功编译安装 sam2-1.1.0）
+   - 修正 `config.py` 中 `sam_model_config` 为 `configs/sam2/sam2_hiera_t.yaml`（Hydra 包内相对路径）
+   - 验证 `torch.cuda.is_available()` → True，RTX 4090 识别正常
+2. **视频封面**：
+   - `frame_parser.py` 新增 `extract_thumbnail()`，从视频第一帧提取 640px JPEG 封面
+   - `media.py` `parse_media()` 解析视频时自动上传封面到 `projects/{id}/thumbnail.jpg`
+   - `projects.py` 返回 presigned URL
+   - 前端 `ProjectLibrary.tsx` 卡片背景显示 `<img>` 封面
+3. **真实帧率 + 可修改解析帧率**：
+   - `models.py` Project 新增 `original_fps` (Float), `parse_fps` (Float, default=30)
+   - `frame_parser.py` `get_video_fps()` 用 OpenCV 读取真实帧率，`parse_video()` 返回 `(frames, original_fps)`
+   - 前端 `ProjectLibrary.tsx` 上传视频时弹窗允许用户滑动设置 parse_fps (1-60)
+   - 项目卡片显示 `原 60.0fps` 和 `30FPS` 标签
+4. **DICOM 批量导入**：
+   - `models.py` Project 新增 `source_type` (video | dicom)
+   - `media.py` 新增 `/api/media/upload/dicom` 接口，接收 `List[UploadFile]`，上传多个 .dcm 到 `uploads/{id}/dicom/`
+   - `media.py` `parse_media()` 支持 DICOM 模式：从 MinIO 下载整个 dicom 目录 → `parse_dicom()` 解析
+   - 前端 `ProjectLibrary.tsx` 导入按钮展开菜单：导入视频 / 导入 DICOM 序列，DICOM 用 `<input multiple accept=".dcm">`
+
+### D. 后续如何避免问题
+1. **SAM2 配置路径必须用 Hydra 包内相对路径**：`build_sam2()` 使用 Hydra，配置文件必须传 `configs/sam2/xxx.yaml` 而非绝对路径
+2. **数据库 schema 变更必须彻底清理旧表**：PostgreSQL `drop_all()` 可能因外键约束不彻底，生产环境应使用 Alembic 迁移，开发环境应手动 `DROP TABLE ... CASCADE`
+3. **大依赖安装必须预留足够磁盘空间**：PyTorch CUDA (~1GB) + SAM2 build (~500MB temp) 至少需要 5GB 可用空间
+4. **前端上传交互必须区分媒体类型**：视频和 DICOM 的上传流程、文件选择器 `accept`、后续解析逻辑完全不同，应提供明确的模式切换
+
+---
+
 ## 2026-04-29-23-28-13 — 视频帧显示链路全修复
 
 ### A. 具体问题

工程分析/需求分析-20260430_001744.md

@@ -0,0 +1,39 @@
+# 需求分析 — 2026-04-30
+
+## 需求背景
+磁盘已扩容至 184GB，空间充足。用户提出 4 个核心需求：
+
+## 需求拆解
+
+| 编号 | 需求 | 优先级 | 影响面 |
+|------|------|--------|--------|
+| R1 | 安装完整版 PyTorch CUDA + SAM2，恢复 GPU 推理 | P0 | conda 环境 |
+| R2 | 项目库视频显示封面缩略图 | P0 | backend/media.py, ProjectLibrary.tsx |
+| R3 | 项目库显示原始帧率，支持修改解析帧率 | P0 | backend/models.py, frame_parser.py, 前端 |
+| R4 | DICOM 连续帧批量导入支持 | P0 | backend/media.py, ProjectLibrary.tsx |
+
+### R1 — PyTorch CUDA + SAM2
+- 当前 PyTorch 为 CPU 版本 (2.11.0+cpu)
+- SAM2 未安装
+- GPU: RTX 4090 24GB，驱动 595.58.03
+- 目标: 安装 PyTorch 2.5+ CUDA 12.4 + SAM2，使 `/api/ai/predict` 使用真实 SAM2 推理
+
+### R2 — 视频封面
+- 当前项目卡片只显示 Film 图标，无封面
+- 目标: 解析视频时提取第一帧作为封面 thumbnail，项目库显示为卡片背景图
+
+### R3 — 帧率显示与修改
+- 当前 fps 为硬编码 "30FPS"
+- 目标: 
+  - 解析视频时读取真实原始帧率，存入 Project.original_fps
+  - 项目库显示原始帧率
+  - 支持设置 parse_fps（解析帧率，可低于原始帧率）
+  - 后端解析时按 parse_fps 提取帧
+
+### R4 — DICOM 批量导入
+- Data_Dicom帧/ 下有 300 个 .dcm 文件，共约 160MB
+- 目标:
+  - 项目类型支持 `source_type`: video / dicom
+  - 导入时支持多选 .dcm 文件批量上传
+  - 上传后解析为帧序列
+  - 支持后续继续向同一项目新增 .dcm 文件