💻 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.

yield

Pythonchilar bilasizmi bu nima?

🏆 Diqqat Musobaqa 🏆

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🤖 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)

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)

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

Umumiy natija

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Natija nima chiqishini kod yozmasdan taxmin qiling.

Kutib oling sun'iy intellekt Uzbek Plov nomli qo'shiq aytdi.

https://youtu.be/Jtv06BQ-CBg

Pythonda kod yozib ppt yasay olasizmi?

Qiziqmi?

Bir ishlatib ko'ringlarchi.

from pptx import Presentation
from pptx.util import Inches, Pt

# Create a presentation object
prs = Presentation()

# Define slides content
slides_content = [
    {"title": "Introduction to Python", "content": "The Versatile Programming Language\nYour Name or Center’s Name"},
    {"title": "What is Python?", 
     "content": "• Python is a high-level, interpreted programming language.\n• Known for its simplicity and readability.\n• Created by Guido van Rossum and first released in 1991."},
    {"title": "Key Features of Python", 
     "content": "• Easy to read and write; syntax is beginner-friendly.\n• Open-source and free to use.\n• Supports multiple programming paradigms (object-oriented, procedural, functional).\n• Extensive standard library and strong community support."},
    {"title": "Why Learn Python?", 
     "content": "• Widely used in web development, data science, AI, automation, and more.\n• High demand in the job market.\n• Large ecosystem with libraries for various tasks.\n• Beginner-friendly, with a fast learning curve."},
    {"title": "Python Syntax Basics", 
     "content": "• Variables and Data Types (int, float, string, list, dictionary)\n• Basic Syntax Example:\nname = 'Python'\nprint('Hello, ' + name)\n• Indentation for defining blocks (no braces or semicolons needed)."},
    {"title": "Popular Python Libraries", 
     "content": "• Data Science: NumPy, pandas, Matplotlib\n• Web Development: Django, Flask\n• Machine Learning & AI: TensorFlow, scikit-learn\n• Automation: Selenium, BeautifulSoup"},
    {"title": "Python Applications", 
     "content": "• Web Development\n• Data Analysis and Visualization\n• Machine Learning and Artificial Intelligence\n• Game Development\n• Scripting and Automation"},
    {"title": "Career Opportunities with Python", 
     "content": "• Python Developer\n• Data Scientist\n• Machine Learning Engineer\n• Web Developer\n• DevOps Engineer"},
    {"title": "Resources to Learn Python", 
     "content": "• Python documentation: https://docs.python.org\n• Online platforms: Codecademy, Coursera, edX, Udacity\n• Books: 'Python Crash Course,' 'Automate the Boring Stuff with Python'"},
    {"title": "Summary", 
     "content": "Why Python is a great language to learn.\nEncouragement to start coding and exploring Python."},
]

# Add slides
for slide_info in slides_content:
    slide_layout = prs.slide_layouts[1]  # Using the Title and Content layout
    slide = prs.slides.add_slide(slide_layout)
    title = slide.shapes.title
    content = slide.placeholders[1]

    # Set title and content for each slide
    title.text = slide_info["title"]
    content.text = slide_info["content"]

# Save the presentation
pptx_path = "Introduction_to_Python_Presentation.pptx"
prs.save(pptx_path)
print(f"Presentation saved as {pptx_path}")

Tez orada: online, tekin telegram bot darslarini boshlimiz.
Ungacha esa siz python dasturlash tilini o'rganib turing.