, Python CUDA , PyTorch , cudatoolkit , Python , PyTouch, cuda cudnn , cudnn cudnn64_8.dll, , model.apex.dummy.pt , 20ms-30ms, model.apex.dummy.engine , , 20ms , , : . STEP 1: Make a visited vector ( vector < int > visited ) and assign all the values to 0 . * @param {string[]} strs . BYolov5-5.0, , , , , Yolov5-6.2, , (cpu). 1143https://leetcode-cn.com/problems/longest-common-subsequence/ 2 , 100 , (2), : 100 , Shift , 10 , , : , , , , : , , . ASCII 1char . PrimKrusakl PrimKruskalKruskalPrimKrusalPrim . , , 4, b2/4, 1, a , 基准移动量, , a . 不再需要使用 C++ 构建生成 .pt .engine , nvidia-tensorrt , nvidia-tensorrt . toolkit.py . This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Run prim's algorithm to get the minimum cost of the tree (number of edges) The answer is total edge number - tree edge number. /test - - (gitee.com), /* Prim's algorithm finds the subset of edges that includes every vertex of the graph such that the sum of the weights of the edges can be minimized. ace abcde aec abcde "ace" "abcde" "aec" "abcde" 5.0, conda , yolov5 6.2 , pycharm workspace, pycharm , , detect.py, , (), , YOLO V5 CPU , GPU , , CUDA Nvidia , Nvidia 2080 8G, , PyTorch CUDA , , CUDA , 3 CUDA , CUDA, Windows, 516.31, CUDA 11.7.1, 516.01, 11.7, 511.23, 11.6, . mid = (high + low) / 2target arr[mid], 3.1 target < arr[mid]high = mid + 12, 3.2 target > arr[mid]low = mid + 12, nums target target , x x true false , 2 II 1 12 XII X + II 27 XXVII, XX + V + II , 2 II 1 12 XII X + II 27 XXVII, XX + V + II , 4 IIII IV 1 5 5 1 4 9 IX, IVIXV - I, /** 0102 Are you sure you want to create this branch? Cache . ace abcde aec abcde , , , , FOV , ADS 1 , FOV FOV , , ADS 1 , . BFSDFS(Dijkstra)(Floyd)Primleetcode 1584 (prim+priority_queue)Kruskalleetcode 1584 (Kruskal UnionFind)Topologicalsortleetcode 133 (DFS + DeepCopy + ShadowCopy . KMeans Inertia Inertia Inertia Inertia, 1 Inertia 0 Inertia 2 Inertia , 3 k k Inertia , 4Inertia , 1 a2b, b a, (-1,1)1 1 a02 0 a=b3. .pt .engine, 上文 - 环境准备 - 操纵键鼠 , , . ace abcde aec abcde , while True 100ms , , , , , . , , , 1000, , , , , . , , , shift+, , . 51c0 a1 b2, , , Apex , FOV , a , 2 / ADS 1 DPI , 360 , , , ? nvidia-pyindex , model.apex.dummy.pt, model.apex.dummy.engine, , , .engine , . a123bc34d8ef34 " 123 34 8 34" 123348 34 , word = a123bc34d8ef34 3 12334 8 34 , word = a1b01c001 1 101 001 , 1 <= word.length <= 1000 word , , , , 5, 1/4, 30, , 50, , 5-30 , , , . CPUCache CacheCache Internet. pip , win32ui , conda , , , conda , DXGI GPU , GPU , D3DShot , D3DShot , D3DShot Python 3.9 pillow , , AMD R7 2700X, Nvidia 2080(8G), 3440*1440, 100(ms), , MSSWin32D3DShotGPU 404422GPU 455849GPU 1/9(33, 1147480) 101023GPU 1/9 101025GPU 1/21(73, 492480) 101022GPU 1/21101023Apex 1/21 101062Apex 1/21 101062, , 250, 4, . , YOLO V5 从 v6.0 起, 官方自带 export.py 工具可以将 .pt 权重文件转换成其他格式, 包括 TensorRT 的 .engine. , , R301//, 80, 100. text1 = "abcde", te } , , , , FOV , , , , PID , PID , , , , , , , , PID , , , (), 8ms, 25ms, , PID , PID , OpencvPySource Kalman filter, predict the trajectory of an Object, , , , B , Mod, , , , , , , , , , , . text1 text2 0 , (, ), , 10ms , 20ms , , weights: ROOT / yolov5s.pt , yolov5s.pt , , project: default=D:\resource\develop\python\dataset.yolo.v5\apex\dummy\runs\train, (, 60 , , ), ( 250 , , ), (, 3440,1440 , 492,480 ), API, GPU, DXGI(GPU), GDI(CPU)(MSS/Win32). K , sklearn metrics silhouette_score metrics silhouette_sample 1 , 0.5150064498560357array([ 0.62982017, 0.5034877 , 0.56148795, 0.84881844, 0.56034142, 0.78740319, 0.39254042, 0.4424015 , 0.48582704])4K, K-Means Kmeans inertia init , K-Means 2007Arthur, David, and Sergei Vassilvitskiikmeans++:The advantages of careful seeding k-means ++, k-means++ random n 1k-means++2k-means++ K 3random 4 n (n_clusters n_features), Original: https://blog.csdn.net/oxygensss/article/details/117093463Author: sssTitle: -, https://www.johngo689.com/221001/, D3DShot Issues#44 Bump pillow version for Python 3.9 support on Windows, yolov5ai, GitHub APEX-yolov5-aim-assist (), PySource Kalman filter, predict the trajectory of an Object, ((Ridge) Lasso), RocketMQRocketMQMMAP, OUTRAGEOUSLY LARGE NEURAL NETWORKS: THE SPARSELY-GATED MIXTURE-OF-EXPERTS LAYER, Pytorch22 CoraGAT, pandasError tokenizing data. Java notes for coding purpose, It contains all the methods and function with their implementations and example for better understanding. , default=, batch-size: GPU, , , , project: default=D:\resource\develop\python\dataset.yolo.v5\test\runs/train, , weights: D:\resource\develop\python\dataset.yolo.v5\test\runs\train\exp\weights\best.pt, 10000 (: 1500head, head10000), (: ), , (, ), , (, , ), (), (FP) , , , 300, 300(, ), , , , 640, , 1280, , , , batch-size. 这里 classes 中的 names 注意顺序要和 labelimg 中的顺序一致, 不然训练出来的模型, 类别是不对的 train.py train.for.apex.dummy.py parse_opt , OSError: [WinError 1455], C70G, 10G, 40G, 50G, , , 60G. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. AB , AOB ( FOV), C (), X(, ), X ? 这里有一个坑需要注意, 不要自己新建文件夹, 就和其他 yolo 文件放在一起, 通过文件名前缀来区分. } c/c++, , 6-7G, c++ , pycocotools , Lib/site-packages , , pycocotools-windows, 3.8Python, : 6.0 /models/common.py , class SPPF , import warnings, Original: https://blog.csdn.net/mrathena/article/details/126860226Author: mrathenaTitle: Python Apex YOLO V5 6.2 , . text1 text2 0 . MST USING PRIM ALGORITHM. 1100110011110001010 If most of the samples in a cluster have a higher profile coefficient, the cluster will have a higher total profile coefficient, and the higher the average profile coefficient of the whole data set, the clustering is appropriate. https://mp.weixin.qq.com/s?__biz=Mzg3Mzc0NjUzMQ==&mid=2247497090&idx=1&sn=417f4d570deb4d116dabb9a473ebdf7a&source=41#wechat_redirect https://mp.weixin.qq.com/s?__biz=Mzg3Mzc0NjUzMQ==&mid=2247497088&idx=1&sn=35e4f21d431d3c6ff91c2d6b62451339&source=41#wechat_redirect https://www.cnblogs.com/huansky/p/13488234.html https://mp.weixin.qq.com/s?__biz=Mzg3Mzc0NjUzMQ==&mid=2247497066&idx=1&sn=1b62c9b5305576a06208b1a2202c9ea7&source=41#wechat_redirect https://leetcode.cn/leetbook/read/binary-search/x6q6fi/, BFS DFS https://www.bilibili.com/video/BV1P5411N7Xc, https://leetcode-cn.com/problems/design-underground-system/ https://leetcode-cn.com/problems/design-authentication-manager/ https://leetcode-cn.com/problems/seat-reservation-manager/ https://leetcode-cn.com/problems/design-twitter/ http://3ms.huawei.com/km/groups/3803117/blogs/details/10397189?l=zh-cn, http://oj.rnd.huawei.com/problems/374/submissions http://oj.rnd.huawei.com/problems/1904/details https://leetcode-cn.com/problems/bianry-number-to-string-lcci/ https://leetcode-cn.com/problems/longest-palindromic-substring/ https://leetcode-cn.com/problems/restore-ip-addresses/ https://leetcode-cn.com/problems/basic-calculator-ii/, http://oj.rnd.huawei.com/problems/395/details http://oj.rnd.huawei.com/problems/282/details https://leetcode-cn.com/problems/fu-za-lian-biao-de-fu-zhi-lcof/ https://leetcode-cn.com/problems/top-k-frequent-words/ https://leetcode-cn.com/problems/find-the-most-competitive-subsequence/ https://leetcode-cn.com/problems/swapping-nodes-in-a-linked-list/, https://leetcode-cn.com/problems/decode-string/ https://leetcode-cn.com/problems/daily-temperatures/solution/ https://leetcode-cn.com/problems/smallest-subsequence-of-distinct-characters/ https://leetcode-cn.com/problems/number-of-islands/ https://leetcode-cn.com/problems/redundant-connection/ https://leetcode-cn.com/problems/minimum-size-subarray-sum/, https://leetcode-cn.com/problems/swap-nodes-in-pairs/ https://leetcode-cn.com/problems/binary-tree-preorder-traversal/ https://leetcode-cn.com/problems/lowest-common-ancestor-of-a-binary-tree/ https://leetcode-cn.com/problems/letter-combinations-of-a-phone-number/ https://leetcode-cn.com/problems/longest-substring-with-at-least-k-repeating-characters/ https://leetcode-cn.com/problems/partition-to-k-equal-sum-subsets/, https://leetcode-cn.com/problems/maximum-width-of-binary-tree/ https://leetcode-cn.com/problems/reorder-routes-to-make-all-paths-lead-to-the-city-zero/ https://leetcode-cn.com/problems/binary-tree-level-order-traversal/ https://leetcode-cn.com/problems/maximum-difference-between-node-and-ancestor/ https://oj.rnd.huawei.com/problems/326/details https://oj.rnd.huawei.com/problems/216/details, BFSDFS https://leetcode-cn.com/problems/flatten-binary-tree-to-linked-list/solution/ https://leetcode-cn.com/problems/course-schedule/solution/ https://leetcode-cn.com/problems/perfect-squares/ https://leetcode-cn.com/problems/course-schedule/ https://oj.rnd.huawei.com/problems/387/details https://oj.rnd.huawei.com/problems/1905/details, https://oj.rnd.huawei.com/problems/290/details https://leetcode-cn.com/problems/task-scheduler/ https://leetcode-cn.com/problems/house-robber/ https://leetcode-cn.com/problems/boats-to-save-people/ https://leetcode-cn.com/problems/house-robber-iii/ http://oj.rnd.huawei.com/problems/221/details, https://mp.weixin.qq.com/s?__biz=Mzg3Mzc0NjUzMQ==&mid=2247497090&idx=1&sn=417f4d570deb4d116dabb9a473ebdf7a&source=41#wechat_redirect, https://mp.weixin.qq.com/s?__biz=Mzg3Mzc0NjUzMQ==&mid=2247497088&idx=1&sn=35e4f21d431d3c6ff91c2d6b62451339&source=41#wechat_redirect, https://mp.weixin.qq.com/s?__biz=Mzg3Mzc0NjUzMQ==&mid=2247497066&idx=1&sn=1b62c9b5305576a06208b1a2202c9ea7&source=41#wechat_redirect, for(size_t i=0;i