Initial commit after resetting Git history

.gitattributes

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+kunin-dlc-240814/dlc-models/iteration-0/demoAug14-trainset95shuffle0/train/snapshot-20000.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
+kunin-dlc-240814/dlc-models/iteration-0/demoAug14-trainset95shuffle0/train/snapshot-20000.meta filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+# 使用 TensorFlow 官方的 GPU 镜像，2.10.0-gpu
+FROM tensorflow/tensorflow:2.10.0-gpu
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# 替换为BFSU的镜像源并安装系统依赖
+RUN sed -i 's|http://archive.ubuntu.com/ubuntu/|https://mirrors.bfsu.edu.cn/ubuntu/|g' /etc/apt/sources.list && \
+    apt-get update -yy && \
+    apt-get install -yy --no-install-recommends ffmpeg libsm6 libxext6 && \
+    rm -rf /var/lib/apt/lists/* && \
+    apt-get clean
+
+# 设置pip使用BFSU的PyPI镜像源并安装Python库和DeepLabCut
+RUN pip config set global.index-url https://mirrors.bfsu.edu.cn/pypi/web/simple && \
+    pip install "deeplabcut[tf]" numpy==1.24.0 decorator==4.4.2 fastapi uvicorn && \
+    pip list
+
+# 修复 TensorFlow 与 protobuf 的兼容性问题
+RUN pip install protobuf==3.20.1
+
+# 修复容器权限问题，确保 DeepLabCut 可以正确运行
+RUN chmod a+rwx -R /usr/local/lib/python3.*/dist-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained
+
+# 复制 kunin-dlc-240814 目录到容器中
+COPY kunin-dlc-240814 /app/kunin-dlc-240814
+
+# 复制应用代码
+COPY app.py /app/app.py
+
+# 设置工作目录
+WORKDIR /app
+
+# 运行服务
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8080"]

app.py

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+import logging
+import asyncio
+from fastapi import FastAPI, HTTPException, Request
+from fastapi.responses import FileResponse
+from fastapi.middleware.cors import CORSMiddleware
+import deeplabcut as dlc
+import os
+import requests
+from typing import Dict
+import threading
+
+# 实例化FastAPI应用
+app = FastAPI()
+
+# 允许任何来源的CORS请求
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # 允许任何来源
+    allow_credentials=True,
+    allow_methods=["*"],  # 允许所有方法
+    allow_headers=["*"],  # 允许所有头部
+)
+
+# 配置文件路径
+project_path = "/app/kunin-dlc-240814"
+config_path = os.path.join(project_path, "config.yaml")
+
+# 设置日志记录格式
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# 创建线程锁
+lock = threading.Lock()
+
+# 用于跟踪已下载的文件
+downloaded_files = {}
+
+@app.post("/analyze")
+async def analyze_video(request: Request):
+    logging.info("Received request for video analysis")
+
+    # 获取锁，确保只有一个分析任务在进行
+    with lock:
+        try:
+            # 在开始处理前清空工作目录
+            clear_working_directory("/app/working")
+
+            data: Dict = await request.json()
+            logging.info(f"Request data: {data}")
+        except Exception as e:
+            logging.error(f"Failed to parse JSON: {str(e)}")
+            raise HTTPException(status_code=400, detail=f"Invalid JSON: {str(e)}")
+
+        if 'videoUrl' not in data or 'videoOssId' not in data:
+            logging.error("Missing videoUrl or videoOssId in request")
+            raise HTTPException(status_code=400, detail="videoUrl and videoOssId are required")
+
+        video_url = data['videoUrl']
+        video_oss_id = data['videoOssId']
+
+        try:
+            video_path = download_video(video_url, video_oss_id)
+            logging.info(f"Downloaded video to: {video_path}")
+        except Exception as e:
+            logging.error(f"Error downloading video: {str(e)}")
+            raise HTTPException(status_code=500, detail=f"Error downloading video: {str(e)}")
+
+        try:
+            # 执行推理
+            logging.info(f"Starting analysis for video: {video_path}")
+            dlc.analyze_videos(config_path, [video_path], shuffle=0, videotype="mp4", auto_track=True)
+            logging.info("Video analysis completed")
+
+            # 过滤预测结果
+            logging.info(f"Filtering predictions for video: {video_path}")
+            dlc.filterpredictions(config_path, [video_path], shuffle=0, videotype='mp4')
+            logging.info("Predictions filtered")
+
+            # 创建标注视频
+            logging.info(f"Creating labeled video for: {video_path}")
+            dlc.create_labeled_video(
+                config_path,
+                [video_path],
+                videotype='mp4',
+                shuffle=0,
+                color_by="individual",
+                keypoints_only=False,
+                draw_skeleton=True,
+                filtered=True,
+            )
+            logging.info("Labeled video created")
+
+            # 查找并重命名输出文件
+            labeled_video_path, h5_file_path = find_and_rename_output_files(video_path)
+            if not labeled_video_path or not h5_file_path:
+                logging.error("Output files missing after analysis")
+                raise HTTPException(status_code=500, detail="Analysis completed, but output files are missing.")
+
+            # 初始化文件下载状态
+            downloaded_files[os.path.basename(labeled_video_path)] = False
+            downloaded_files[os.path.basename(h5_file_path)] = False
+
+        except Exception as e:
+            logging.error(f"Error during video analysis: {str(e)}")
+            raise HTTPException(status_code=500, detail=f"Error during video analysis: {str(e)}")
+
+        response_data = {
+            "videoOssId": video_oss_id,
+            "labeled_video": f"/post_download/{os.path.basename(labeled_video_path)}",
+            "h5_file": f"/post_download/{os.path.basename(h5_file_path)}"
+        }
+
+        logging.info("Returning response data")
+        return response_data
+
+@app.post("/post_download/{filename}")
+async def post_download_file(filename: str):
+    file_path = os.path.join("/app/working", filename)
+    if os.path.exists(file_path):
+        # 标记文件已被下载
+        downloaded_files[filename] = True
+        logging.info(f"Serving file: {file_path}")
+        return FileResponse(path=file_path, media_type='application/octet-stream', filename=filename)
+    else:
+        raise HTTPException(status_code=404, detail="File not found")
+
+async def wait_for_files_to_be_downloaded(files: list):
+    """等待文件被访问和下载后删除"""
+    try:
+        while any(not downloaded_files.get(os.path.basename(file), False) for file in files):
+            logging.info(f"Waiting for files to be downloaded: {files}")
+            await asyncio.sleep(5)
+        logging.info("All files have been downloaded, deleting them...")
+        for file in files:
+            if os.path.exists(file):
+                os.remove(file)
+                logging.info(f"Deleted file: {file}")
+        logging.info("All files have been deleted.")
+    except Exception as e:
+        logging.error(f"Failed to wait for files: {str(e)}")
+
+def find_and_rename_output_files(video_path: str):
+    """查找并重命名生成的标注视频和H5文件"""
+    working_directory = "/app/working"
+    base_name = os.path.splitext(os.path.basename(video_path))[0]
+
+    labeled_video = None
+    h5_file = None
+
+    for file in os.listdir(working_directory):
+        if file.endswith("_id_labeled.mp4"):
+            labeled_video = os.path.join(working_directory, file)
+            new_labeled_video = os.path.join(working_directory, f"{base_name}_labeled.mp4")
+            os.rename(labeled_video, new_labeled_video)
+            labeled_video = new_labeled_video
+            logging.info(f"Renamed labeled video to: {labeled_video}")
+        elif file.endswith("_filtered.h5"):
+            h5_file = os.path.join(working_directory, file)
+            new_h5_file = os.path.join(working_directory, f"{base_name}.h5")
+            os.rename(h5_file, new_h5_file)
+            h5_file = new_h5_file
+            logging.info(f"Renamed H5 file to: {h5_file}")
+
+    logging.info(f"Files in working directory after video processing: {os.listdir(working_directory)}")
+    return labeled_video, h5_file
+
+def download_video(url: str, video_oss_id: str) -> str:
+    working_directory = "/app/working"
+    
+    try:
+        # 确保目标目录存在
+        if not os.path.exists(working_directory):
+            os.makedirs(working_directory)
+
+        # 使用video_oss_id作为文件名，避免命名冲突
+        local_filename = os.path.join(working_directory, f"{video_oss_id}.mp4")
+        
+        # 下载视频并处理可能的连接错误
+        logging.info(f"Downloading video from URL: {url}")
+        with requests.get(url, stream=True, timeout=60) as r:
+            r.raise_for_status()
+            with open(local_filename, 'wb') as f:
+                for chunk in r.iter_content(chunk_size=8192):
+                    if chunk:  # 过滤掉保持连接的空块
+                        f.write(chunk)
+        logging.info(f"Video downloaded to: {local_filename}")
+        return local_filename
+    
+    except requests.exceptions.RequestException as e:
+        logging.error(f"Failed to download video: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to download video: {str(e)}")
+    except Exception as e:
+        logging.error(f"Unexpected error: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Unexpected error: {str(e)}")
+
+def clear_working_directory(directory: str):
+    """清空工作目录中的所有文件"""
+    try:
+        for filename in os.listdir(directory):
+            file_path = os.path.join(directory, filename)
+            if os.path.isfile(file_path) or os.path.islink(file_path):
+                os.unlink(file_path)
+            elif os.path.isdir(file_path):
+                os.rmdir(file_path)
+        logging.info(f"Cleared all files in directory: {directory}")
+    except Exception as e:
+        logging.error(f"Failed to clear directory {directory}: {str(e)}")
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8080)

kunin-dlc-240814/config.yaml

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+    # Project definitions (do not edit)
+Task: demo
+scorer: me
+date: Aug14
+multianimalproject: true
+identity:
+
+    # Project path (change when moving around)
+project_path: /app/kunin-dlc-240814
+
+    # Annotation data set configuration (and individual video cropping parameters)
+video_sets:
+  /Users/placeholder.mp4:
+    crop: 0, 400, 0, 400
+individuals:
+- mus1
+uniquebodyparts: []
+multianimalbodyparts:
+- snout
+- leftear
+- rightear
+- shoulder
+- spine1
+- spine2
+- spine3
+- spine4
+- tailbase
+- tail1
+- tail2
+- tailend
+bodyparts:
+- snout
+- leftear
+- rightear
+- shoulder
+- spine1
+- spine2
+- spine3
+- spine4
+- tailbase
+- tail1
+- tail2
+- tailend
+
+    # Fraction of video to start/stop when extracting frames for labeling/refinement
+
+    # Fraction of video to start/stop when extracting frames for labeling/refinement
+start: 0
+stop: 1
+numframes2pick: 16
+
+    # Plotting configuration
+skeleton:
+- - snout
+  - leftear
+- - snout
+  - rightear
+- - snout
+  - tailbase
+
+
+skeleton_color: cyan
+pcutoff: 0.01
+dotsize: 3
+alphavalue: 0.7
+colormap: spring
+
+    # Training,Evaluation and Analysis configuration
+TrainingFraction:
+- 0.95
+iteration: 0
+default_net_type: resnet_50
+default_augmenter: default
+default_track_method: ellipse
+snapshotindex: -1
+batch_size: 8
+
+    # Cropping Parameters (for analysis and outlier frame detection)
+cropping: false
+    #if cropping is true for analysis, then set the values here:
+x1: 0
+x2: 640
+y1: 277
+y2: 624
+
+    # Refinement configuration (parameters from annotation dataset configuration also relevant in this stage)
+corner2move2:
+- 50
+- 50
+move2corner: true
+croppedtraining: true
+resnet: 50

kunin-dlc-240814/dlc-models/iteration-0/demoAug14-trainset95shuffle0/test/inference_cfg.yaml

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+addlikelihoods: 0.15
+averagescore: 0.1
+boundingboxslack: 0
+detectionthresholdsquare: 0.1
+distnormalization: 1000
+distnormalizationLOWER: 0
+iou_threshold: 0.6
+lowerbound_factor: 0.5
+max_age: 1
+method: m1
+min_hits: 1
+minimalnumberofconnections: 6
+pafthreshold: 0.1
+topktoretain: 3
+upperbound_factor: 1.25
+variant: 0
+withid: false

kunin-dlc-240814/dlc-models/iteration-0/demoAug14-trainset95shuffle0/test/pose_cfg.yaml

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+all_joints:
+- - 0
+- - 1
+- - 2
+- - 3
+- - 4
+- - 5
+- - 6
+- - 7
+- - 8
+- - 9
+- - 10
+- - 11
+all_joints_names:
+- snout
+- leftear
+- rightear
+- shoulder
+- spine1
+- spine2
+- spine3
+- spine4
+- tailbase
+- tail1
+- tail2
+- tailend
+dataset: training-datasets/iteration-1/UnaugmentedDataSet_MultiMouseDec16/MultiMouse_Daniel95shuffle0.pickle
+dataset_type: multi-animal-imgaug
+global_scale: 0.8
+init_weights: /home/alex/anaconda3/envs/DLC-GPU/lib/python3.7/site-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_50.ckpt
+location_refinement: true
+locref_stdev: 7.2801
+minconfidence: 0.01
+net_type: resnet_50
+nmsradius: 5.0
+num_joints: 12
+num_limbs: 66
+pairwise_predict: false
+partaffinityfield_graph:
+- - 0
+  - 1
+- - 0
+  - 2
+- - 0
+  - 3
+- - 0
+  - 4
+- - 0
+  - 5
+- - 0
+  - 6
+- - 0
+  - 7
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+  - 10
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+  - 11
+- - 10
+  - 11
+partaffinityfield_predict: 'True'
+scoremap_dir: test
+project_path: /home/jessy/DeepLabCut/demo-me-2021-07-14
+bank3: 128
+bank5: 128
+smfactor: 4
+stride: 4
+multi_stage: true
+paf_best:
+- 30
+- 38
+- 39
+- 46
+- 21
+- 12
+- 63
+- 57
+- 56
+- 65
+- 2
+- 51
+- 40
+- 45
+- 22
+- 31
+- 33

kunin-dlc-240814/dlc-models/iteration-0/demoAug14-trainset95shuffle0/train/pose_cfg.yaml

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+all_joints:
+- - 0
+- - 1
+- - 2
+- - 3
+- - 4
+- - 5
+- - 6
+- - 7
+- - 8
+- - 9
+- - 10
+- - 11
+all_joints_names:
+- snout
+- leftear
+- rightear
+- shoulder
+- spine1
+- spine2
+- spine3
+- spine4
+- tailbase
+- tail1
+- tail2
+- tailend
+batch_size: 4
+cropratio: 0.6
+dataset: training-datasets/iteration-1/UnaugmentedDataSet_MultiMouseDec16/MultiMouse_Daniel95shuffle0.pickle
+dataset_type: multi-animal-imgaug
+init_weights: /media/data/mu/MultiMouse-Daniel-2019-12-16/multistage5_single-shortcut-3M-DLC-benchmarkinghr_stride4_fc_p20/dlc-models/iteration-1/MultiMouseDec16-trainset95shuffle0/train/snapshot-60000
+display_iters: 100
+global_scale: 0.8
+intermediate_supervision: false
+intermediate_supervision_layer: 12
+location_refinement: true
+locref_huber_loss: true
+locref_loss_weight: 0.05
+locref_stdev: 7.2801
+max_input_size: 1500
+metadataset: training-datasets/iteration-1/UnaugmentedDataSet_MultiMouseDec16/Documentation_data-MultiMouse_95shuffle0.pickle
+min_input_size: 64
+mirror: false
+multi_step:
+- - 0.0001
+  - 7500
+- - 5e-05
+  - 12000
+- - 1e-05
+  - 500000
+net_type: resnet_50
+num_joints: 12
+num_limbs: 66
+optimizer: adam
+pafwidth: 12
+pairwise_huber_loss: false
+pairwise_loss_weight: 1
+pairwise_predict: false
+partaffinityfield_graph:
+- - 0
+  - 1
+- - 0
+  - 2
+- - 0
+  - 3
+- - 0
+  - 4
+- - 0
+  - 5
+- - 0
+  - 6
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+  - 11
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+  - 10
+- - 9
+  - 11
+- - 10
+  - 11
+partaffinityfield_predict: true
+pos_dist_thresh: 17
+project_path: /media/data/mu/MultiMouse-Daniel-2019-12-16
+rotation: 180
+rotratio: 0.4
+save_iters: 10000
+scale_jitter_lo: 0.5
+scale_jitter_up: 1.2
+weigh_only_present_joints: false
+augmentationprobability: 0.5
+fliplr: true
+hist_eq: true
+cropfactor: 0.2
+covering: true
+motion_blur:
+- - k
+  - 7
+- - angle
+  - - -90
+    - 90
+elastic_transform: true
+scmap_type: plateau
+bank3: 128
+bank5: 128
+smfactor: 4
+stride: 4
+multi_stage: true

kunin-dlc-240814/dlc-models/iteration-0/demoAug14-trainset95shuffle0/train/snapshot-20000.data-00000-of-00001

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kunin-dlc-240814/dlc-models/iteration-0/demoAug14-trainset95shuffle0/train/snapshot-20000.meta

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