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These are the user uploaded subtitles that are being translated: 1 00:00:00,090 --> 00:00:04,410 In this video, we'll show you how to install YOLO v seven CPU mode on windows. 2 00:00:04,770 --> 00:00:09,120 CPU mode is intended for computers or laptops equipped with an nvidia GPU. 3 00:00:09,540 --> 00:00:11,070 Why should you use TPU? 4 00:00:11,280 --> 00:00:16,800 The reason for this is the GPUs can accelerate the computational process for deep learning resulting 5 00:00:16,800 --> 00:00:18,390 in maximum performance. 6 00:00:19,410 --> 00:00:23,940 The first step is to create an environment, press windows and type in condom. 7 00:00:25,020 --> 00:00:26,730 Click on End Condo Navigator. 8 00:00:31,630 --> 00:00:34,360 If it's already open click environments. 9 00:00:35,600 --> 00:00:39,740 Click create to start creating environments, then enter the environments name. 10 00:00:39,740 --> 00:00:42,890 In this example, we name it Your life is 7 to 4. 11 00:00:42,900 --> 00:00:44,420 You can v. 12 00:00:47,160 --> 00:00:50,910 In Python, select Python 3.10, then click create. 13 00:00:52,520 --> 00:00:54,650 Wait until the environment is finished. 14 00:00:59,900 --> 00:01:01,700 It will look like this when it is finished. 15 00:01:03,210 --> 00:01:05,250 Then open the anaconda prompt. 16 00:01:06,160 --> 00:01:08,500 Address the Windows key, then type in condom. 17 00:01:09,770 --> 00:01:11,240 Click on any kind of prompt. 18 00:01:12,660 --> 00:01:17,370 After that, activate the environment, use the commands, activate. 19 00:01:18,620 --> 00:01:19,970 Your life is 7 to 4. 20 00:01:19,970 --> 00:01:21,440 You can feel. 21 00:01:22,310 --> 00:01:23,330 Then press enter. 22 00:01:24,320 --> 00:01:27,470 If it looks like this, it means that the environment is active. 23 00:01:28,070 --> 00:01:31,970 Then navigate to the directory where the seven source code will be safe. 24 00:01:32,150 --> 00:01:34,880 In this example, it will be stored in a directory. 25 00:01:35,270 --> 00:01:37,820 Use the command D, then press enter. 26 00:01:39,600 --> 00:01:42,480 The next step is to clone the YOLO V7 repository. 27 00:01:42,990 --> 00:01:44,670 First launched a browser. 28 00:01:45,470 --> 00:01:47,550 Then visit the following repository. 29 00:01:47,570 --> 00:01:53,690 The original repository has been forced into this repository to clone copy the repository link using 30 00:01:53,690 --> 00:01:56,000 click code, then click the following button. 31 00:01:58,630 --> 00:02:01,150 If it has been copied back again to the prompt. 32 00:02:02,380 --> 00:02:03,700 Then execute the command. 33 00:02:04,590 --> 00:02:05,340 Declan. 34 00:02:06,040 --> 00:02:07,840 Then trace the repository link. 35 00:02:08,139 --> 00:02:09,009 Press enter. 36 00:02:10,139 --> 00:02:12,390 Wait until the cloning process is finished. 37 00:02:16,150 --> 00:02:20,110 If it is completed, the results will be saved in all of these seven folder. 38 00:02:21,700 --> 00:02:26,980 Since the name of the owner of his seven folder to all of his seven CPU use commands. 39 00:02:27,160 --> 00:02:28,240 When YOLO. 40 00:02:28,260 --> 00:02:28,900 Five seven. 41 00:02:30,190 --> 00:02:31,720 YOLO five seven CPU. 42 00:02:33,570 --> 00:02:36,480 This is the root directory of the seven source code. 43 00:02:36,810 --> 00:02:43,620 Then navigate to the root folder of the role of seven GPU using command city YOLO. 44 00:02:43,620 --> 00:02:46,290 574 you press enter. 45 00:02:49,570 --> 00:02:53,170 Following that, we install patrols which can run on the GPU. 46 00:02:54,380 --> 00:02:58,100 The first step is to launch a browser and navigate to the following URL. 47 00:03:00,260 --> 00:03:01,700 Continue to scroll down. 48 00:03:03,250 --> 00:03:05,500 On titles build select stable version. 49 00:03:06,320 --> 00:03:14,780 Under your OS select windows in packages, select PIP in language, Select Python at just the compute 50 00:03:14,780 --> 00:03:16,750 platform to the installed version of queued. 51 00:03:16,820 --> 00:03:20,870 If nothing matches, choose the first thing that is lower than the installed version of queued. 52 00:03:21,320 --> 00:03:23,750 In this example queue the 11.6. 53 00:03:26,380 --> 00:03:28,090 Here is the installation command. 54 00:03:29,170 --> 00:03:30,170 Copy the command. 55 00:03:30,190 --> 00:03:31,510 With a block like this. 56 00:03:32,170 --> 00:03:34,240 Then right click and select copy. 57 00:03:35,840 --> 00:03:37,440 We turn to the prompt after that. 58 00:03:37,460 --> 00:03:41,120 Then pace the command to install patrols by pressing control fee. 59 00:03:41,810 --> 00:03:42,680 Press enter. 60 00:03:43,970 --> 00:03:46,010 Wait until the installation is finished. 61 00:04:02,280 --> 00:04:04,770 If it looks like this, the installation is finished. 62 00:04:09,090 --> 00:04:14,070 Next install python requirements using the command chip install. 63 00:04:14,830 --> 00:04:16,950 That's are requirements. 64 00:04:17,000 --> 00:04:19,660 If you don't text, press enter. 65 00:04:22,830 --> 00:04:24,840 Wait until the installation is finished. 66 00:04:29,980 --> 00:04:33,520 To test the installation, we will perform object detection on the image. 67 00:04:33,550 --> 00:04:38,170 However, before we begin the detection, we must first download all of these seven weights. 68 00:04:38,410 --> 00:04:39,640 We launched the browser. 69 00:04:43,060 --> 00:04:44,320 Scroll down after the. 70 00:04:46,270 --> 00:04:48,790 Here are some examples of weights that can be used. 71 00:04:50,120 --> 00:04:53,000 We will download with you all of these seven in this example. 72 00:04:57,340 --> 00:04:59,170 Wait until the download is finished. 73 00:05:04,690 --> 00:05:07,750 When you're finished, go to the downloads folder and open the file. 74 00:05:12,250 --> 00:05:15,850 Next move the words to the root folder of the seven Dpu. 75 00:05:17,490 --> 00:05:20,130 Click the weights file, then press control X. 76 00:05:24,390 --> 00:05:28,590 Place in the root folder of 70 CPU by pressing the control button. 77 00:05:30,890 --> 00:05:34,940 YOLO V seven includes a number of sample images that can be used for detection. 78 00:05:35,270 --> 00:05:37,730 Sample image located in the inference. 79 00:05:39,030 --> 00:05:40,080 Images folder. 80 00:05:41,140 --> 00:05:43,720 In this example, we will detect objects on the image. 81 00:05:43,720 --> 00:05:45,070 Horses duct taped. 82 00:05:48,310 --> 00:05:54,340 We return to the Anaconda prompt to perform the detection, execute the command python, detect the 83 00:05:54,370 --> 00:05:55,060 PI. 84 00:05:57,100 --> 00:05:58,930 That's, that's it's, you know, five, seven. 85 00:05:59,760 --> 00:06:00,900 That's their source. 86 00:06:02,640 --> 00:06:07,530 Inference images sources dot jpg press enter. 87 00:06:10,220 --> 00:06:12,590 Wait for the detection process to finish. 88 00:06:15,790 --> 00:06:19,630 When finished, the detection results will be saved in the folder listed below. 89 00:06:21,020 --> 00:06:21,560 To see it. 90 00:06:21,560 --> 00:06:23,180 We open Windows Explorer. 91 00:06:23,940 --> 00:06:29,700 Then go back to the root for the rule of seven TPU, then navigate to the folder containing the detection 92 00:06:29,700 --> 00:06:30,450 results. 93 00:06:32,400 --> 00:06:35,880 The result of object detection using all of seven is shown below. 94 00:06:40,850 --> 00:06:42,770 In the detections and training section. 95 00:06:42,770 --> 00:06:46,610 We will use CPU mode to maximise the performance of the whole of seven. 96 00:06:46,640 --> 00:06:48,230 See you in the next video. 8055

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