All language subtitles for 002 Windows YOLOv7 Object Detection on image (GPU Mode)

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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:01,950 --> 00:00:06,860 In this video, we'll tell you how to use your office seven to detect the object classes in an image. 2 00:00:06,870 --> 00:00:12,450 But first, YOLO v seven must be successfully installed and which must be downloaded to begin. 3 00:00:12,480 --> 00:00:14,910 Press the Windows key then type Anaconda. 4 00:00:17,050 --> 00:00:18,520 Click on any kind of prompt. 5 00:00:22,220 --> 00:00:28,340 After that activate the all of seven CPU environment used to commands activate. 6 00:00:29,030 --> 00:00:31,400 Jollof is seven to for you and phe. 7 00:00:32,200 --> 00:00:33,010 Press internal. 8 00:00:40,330 --> 00:00:43,420 Then navigate to the all of seven zip route folder. 9 00:00:48,150 --> 00:00:53,040 We will detect objects in the image here, but the source is a folder containing several images, not 10 00:00:53,040 --> 00:00:53,970 a single file. 11 00:00:55,040 --> 00:00:56,480 Use the following command. 12 00:00:58,070 --> 00:01:00,260 Python detector PI. 13 00:01:00,920 --> 00:01:01,340 That's. 14 00:01:01,340 --> 00:01:03,170 That's why it's all of seven. 15 00:01:05,910 --> 00:01:08,280 We use 0.5 in contrasts. 16 00:01:12,970 --> 00:01:14,020 In the image size. 17 00:01:14,020 --> 00:01:15,580 We use 640. 18 00:01:21,040 --> 00:01:23,980 In-source we will detect in the inference images folder. 19 00:01:33,040 --> 00:01:34,600 Use the few image argument. 20 00:01:38,100 --> 00:01:39,960 Use the safety argument. 21 00:01:43,080 --> 00:01:43,860 Chris intro. 22 00:01:47,750 --> 00:01:50,120 Went for the detection process to fitness. 23 00:01:58,670 --> 00:02:02,810 Because it uses the few inmates argument, the detection results will appear like this. 24 00:02:05,600 --> 00:02:08,630 The detection results will be saved in the folder listed below. 25 00:02:11,800 --> 00:02:13,750 We open Windows Explorer to see. 26 00:02:16,460 --> 00:02:19,550 Then navigate to the all of 73 use route folder. 27 00:02:21,530 --> 00:02:24,500 Navigate to the folder containing the text and results. 28 00:02:28,580 --> 00:02:31,970 Here are some object detection results obtained with the goal of seven. 29 00:02:38,770 --> 00:02:40,930 Because it uses a 0.5 threshold. 30 00:02:40,960 --> 00:02:45,310 The detection results will only sell objects with a score greater than 0.5. 31 00:02:48,560 --> 00:02:53,120 Then because it uses the safety argument, the detection results are stored in a file. 32 00:02:53,150 --> 00:02:55,280 The file is saved in the labels folder. 33 00:02:57,600 --> 00:03:00,210 This is the file where the text and results are safe. 34 00:03:03,580 --> 00:03:08,110 This file contains the class ID, mid-point, width and height, bounding box information. 35 00:03:19,660 --> 00:03:24,040 The next video will explain how to detect objects on video and webcam. 36 00:03:26,370 --> 00:03:27,840 See you in the next video. 3067

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