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PYTHON DASTURLASH TILI

PYTHON DASTURLASH TILI

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Python dasturlash tilini o'rganmoqchimisiz ? Ammo bu dasturlash tili haqida kerakli ma'lumotlarni qayerdan topishni bilmayabsizmi ? Telegram tarmog'idagi Python dasturlash tili haqida barcha ma'lumotlarni o'zida saqlovchi kanal: @Python_uzbek_coder

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Channel Posts
PYTHON DASTURLASH TILI
Repost from Sardor Salimov | IT teacher
Kutib oling sun'iy intellekt Uzbek Plov nomli qo'shiq aytdi. https://youtu.be/Jtv06BQ-CBg

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Natija nima chiqishini kod yozmasdan taxmin qiling.
Natija nima chiqishini kod yozmasdan taxmin qiling.
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😂😂😂
😂😂😂
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https://www.instagram.com/reel/C5GulqqKTOw/?igsh=MWQ5MWF5NzJlbmx5dg==
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🔠🅰️🔠🅰️🔠🔠🔠 Bot PYTHON dasturlash tilida yaratilgan! Ramazon oyida siz va yaqinlaringiz uchun foydali bot. @PrayingTime_bot Bot orqali siz namoz vaqtlaridan habar topishingiz mumkin. Bundan tashqari bot sizga o'g'iz ochish va og'iz yopish vaqtlarini eslatib turadi.
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No text...
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IT tanlovlarda 1-o'rin uchun qancha pul mukofoti qo'yiladi? Ulug'bek vorislari - 10 mln so'mdan ortiq. Uz data challenge - 50.000$. President Tech Award - 100.000$. StartUP loyihalar tanlovi - 500 mln so'mgacha. Bu tanlovlarda g'olib bo'lish uchun sizda IT loyiha va uning pratatipi bo'lishi kerak. ☎️ +998505004030 👨‍💻 @Algorithmic_Solutions 📍 Firdavsiy 1 (Infin bank)
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Umumiy natija
Umumiy natija
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Agar natija olib kursak cls: tensor([0., 0., 0., 0., 0., 0., 0.]) conf: tensor([0.8909, 0.8682, 0.8674, 0.8622, 0.8439, 0.8392, 0.7159]) data: tensor([[1.6254e+02, 2.2389e+01, 2.5266e+02, 1.6701e+02, 8.9091e-01, 0.0000e+00], [2.3503e+02, 3.1486e+01, 2.9971e+02, 1.6686e+02, 8.6820e-01, 0.0000e+00], [2.1997e+01, 5.3749e+01, 7.4538e+01, 1.6752e+02, 8.6741e-01, 0.0000e+00], [1.1284e+02, 3.2849e+01, 1.6784e+02, 1.6768e+02, 8.6221e-01, 0.0000e+00], [6.3885e+01, 4.3812e+01, 1.1679e+02, 1.6726e+02, 8.4389e-01, 0.0000e+00], [3.2759e-02, 5.2869e+00, 4.6813e+01, 1.6724e+02, 8.3916e-01, 0.0000e+00], [1.5617e+02, 1.0563e+01, 1.9749e+02, 9.0878e+01, 7.1594e-01, 0.0000e+00]]) id: None is_track: False orig_shape: (168, 300) shape: torch.Size([7, 6]) xywh: tensor([[207.5979, 94.6973, 90.1146, 144.6161], [267.3671, 99.1744, 64.6808, 135.3771], [ 48.2676, 110.6329, 52.5402, 113.7673], [140.3382, 100.2657, 55.0010, 134.8336], [ 90.3380, 105.5342, 52.9057, 123.4454], [ 23.4231, 86.2625, 46.7806, 161.9512], [176.8280, 50.7202, 41.3200, 80.3153]]) xywhn: tensor([[0.6920, 0.5637, 0.3004, 0.8608], [0.8912, 0.5903, 0.2156, 0.8058], [0.1609, 0.6585, 0.1751, 0.6772], [0.4678, 0.5968, 0.1833, 0.8026], [0.3011, 0.6282, 0.1764, 0.7348], [0.0781, 0.5135, 0.1559, 0.9640], [0.5894, 0.3019, 0.1377, 0.4781]]) xyxy: tensor([[1.6254e+02, 2.2389e+01, 2.5266e+02, 1.6701e+02], [2.3503e+02, 3.1486e+01, 2.9971e+02, 1.6686e+02], [2.1997e+01, 5.3749e+01, 7.4538e+01, 1.6752e+02], [1.1284e+02, 3.2849e+01, 1.6784e+02, 1.6768e+02], [6.3885e+01, 4.3812e+01, 1.1679e+02, 1.6726e+02], [3.2759e-02, 5.2869e+00, 4.6813e+01, 1.6724e+02], [1.5617e+02, 1.0563e+01, 1.9749e+02, 9.0878e+01]]) xyxyn: tensor([[5.4180e-01, 1.3327e-01, 8.4218e-01, 9.9408e-01], [7.8342e-01, 1.8742e-01, 9.9902e-01, 9.9323e-01], [7.3325e-02, 3.1994e-01, 2.4846e-01, 9.9712e-01], [3.7613e-01, 1.9553e-01, 5.5946e-01, 9.9811e-01], [2.1295e-01, 2.6078e-01, 3.8930e-01, 9.9558e-01], [1.0920e-04, 3.1470e-02, 1.5604e-01, 9.9546e-01], [5.2056e-01, 6.2872e-02, 6.5829e-01, 5.4094e-01]]) Shunga uxshagan natija beradi. Natija siz ishlatayotgan freymworkga bogliq (Pytorch, ....) Demak birinchi listda sinf (0-bu odam umumiy sinflar names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} ) keyin esa conf yane har bitta obektni aniqlash aniqligi ruyxati (rasmda bir nechta obekt buladi) keyin esa bizga obekt joylashuvi xywh yane yuqori chap burchag koordinatasi va w-uzunlik h-balandlik beriladi. bundan tashqari biz turtburchak asosida malumotni olishimiz mumkin yuqori chao va pastgi ong xyxy
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Rasm yoki freymdan malum predmet obekt ni joylashuvni olamiz. Bu ham juda oson 5-6 qatorda bajariladi. from ultralytics impor
Rasm yoki freymdan malum predmet obekt ni joylashuvni olamiz. Bu ham juda oson 5-6 qatorda bajariladi. from ultralytics import YOLO model = YOLO("yolov8s.pt") ans = model.predict(source= ".../person.jpeg", show = True, imgsz = 320, conf = 0.7) #yolov8s bir nechta turdagi obektlarni detection qila oladi for obj in ans: box = obj.boxes print(box)
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🏆 Diqqat Musobaqa 🏆 Pythonchilar diqqatiga. O'z bilimlaringizni sinab ko'ring! 🤖 RoboContest Round #87 div3 va 🤖 RoboCont
🏆 Diqqat Musobaqa 🏆 Pythonchilar diqqatiga. O'z bilimlaringizni sinab ko'ring! 🤖 RoboContest Round #87 div3 va 🤖 RoboContest Round #88 div2 📊 Div3 - reytingi [1000,1500] oralig'idagi ishtirokchilar uchun rated 📊 Div2 - reytingi [1501, ∞] oralig'idagi ishtirokchilar uchun rated Agar reyting mos kelmasa unrated qatnashish imkoni mavjud, ya'ni reyting berilmaydi/ 📆Contest boshlanish vaqti: 05.03.2024 19:30 📆Contest tugash vaqti: 05.03.2024 21:30 ⏰Contest davomiyligi: 2 soat 👨‍🏫 Muallif: Sardor Salimov 💬Agar savollar bo’lsa @robocontest_chat ga murojaat qiling. 🤖🤖🤖🤖🤖 @robocontest #contest #rated (Savollar o'zbekcha va ruscha tillarda bo'ladi)
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#aktivatsiya slmgr/ipk W269N-WFGWX-YVC9B-4J6C9-T83GX slmgr /skms kms.digiboy.ir slmgr /ato
#aktivatsiya slmgr/ipk W269N-WFGWX-YVC9B-4J6C9-T83GX slmgr /skms kms.digiboy.ir slmgr /ato
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yield Pythonchilar bilasizmi bu nima?
yield Pythonchilar bilasizmi bu nima?
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Hozirga qadar kompyuterlar uchun eng ko'p foydalanilgan operatsion tizim qaysi? Какая операционная система для компьютеров на данный момент является наиболее используемой?
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💻 Inson mehnati AI dan ko'ra arzon (hozircha). MIT universitetining tadqiqotlariga qaraganda. Inson sun'iy intellekt robotla
💻 Inson mehnati AI dan ko'ra arzon (hozircha). MIT universitetining tadqiqotlariga qaraganda. Inson sun'iy intellekt robotlariga qaraganda 2 baravar arzon ishchi kuchi hisoblanadi. Buning ustiga insonlar o'z vazifasidan tashqari ishlarni ham bajarishadi... Ammo tadqiqotlar bu uzoq davom etmasligi va yaqin yillarda robotlar arzon ishchi kuchiga aylanishini ko'rsatmoqda.
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Bu rasmlarni nima bog'lab turadi?+9
Bu rasmlarni nima bog'lab turadi?
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emot nima ish qilishini topganga bitta besh😄
emot nima ish qilishini topganga bitta besh😄
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PYTHON qaysi sohada yetakchi deb o'ylaysiz?
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Tez orada python 3.13 chiqadi... https://pythoninsider.blogspot.com/2024/01/python-3130-alpha-3-is-now-available.html
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https://t.me/python_uzbek_coder?boost
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