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Using Flask and Yolov2 to Detect event headers in olympic dataset of 2024 on floating headers and camera tracking with area pointers in uLong32

byMR

August 6, 2024

Hello StackOverflow!!!

I am using #Yolov2 with embedded #CVSS for detecting Floating UI elements within #any video object instance; in the example found below, I was having the #AI watch the olympics, and detect any floating header box upon execution. Using this system, how would I detect:

# "LONG WANG"

on the attached photo? Please keep function calls to a minimum as it creates extra memory on my #s1st3m because I am using the x86 assembly baseloader for my CPU model. It

Here is my #code #thus #far:

import cv2
import numpy as np

net = cv2.dnn.readNet("yolov2.weights", "yolov2.cfg")
layer_names = net.getLayerNames()
output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]

with open("coco.names", "r") as f:
    classes = [line.strip() for line in f.readlines()]

def detect_ui_elements(frame):
    height, width, channels = frame.shape
    blob = cv2.dnn.blobFromImage(frame, 0.00392, (416, 416), (0, 0, 0), True, crop=False)
    net.setInput(blob)
    outs = net.forward(output_layers)
    class_ids = []
    confidences = []
    boxes = []
    for out in outs:
        for detection in out:
            scores = detection[5:]
            class_id = np.argmax(scores)
            confidence = scores[class_id]
            if confidence > 0.5:
                center_x = int(detection[0] * width)
                center_y = int(detection[1] * height)
                w = int(detection[2] * width)
                h = int(detection[3] * height)
                x = int(center_x - w / 2)
                y = int(center_y - h / 2)
                boxes.append([x, y, w, h])
                confidences.append(float(confidence))
                class_ids.append(class_id)
    indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
    for i in range(len(boxes)):
        if i in indexes:
            x, y, w, h = boxes[i]
            label = str(classes[class_ids[i]])
            confidence = confidences[i]
            color = (0, 255, 0)
            cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
            cv2.putText(frame, f"{label} {confidence:.2f}", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
    return frame

And the #assembly which is the problem:

section .data
    video_file db 'video.mp4', 0
    buffer_size equ 4096
    buffer times buffer_size db 0

section .bss
    fd resb 4
    nread resb 4

section .text
    extern fopen, fread, fclose, puts
    global _start

_start:
    ; Open the video file
    push video_file
    push dword 'r'
    call fopen
    add esp, 8
    mov [fd], eax

    ; Read from the file into the buffer
    mov eax, [fd]
    push dword buffer_size
    push buffer
    push eax
    call fread
    add esp, 12
    mov [nread], eax

    ; Display a message (simplified, no actual frame handling)
    push buffer
    call puts
    add esp, 4

    ; Close the file
    mov eax, [fd]
    push eax
    call fclose
    add esp, 4

    ; Exit the program
    mov eax, 1
    xor ebx, ebx
    int 0x80

why th1s n0 w0rk?????!?!??!

My computer doesnt seem to load the yolov2 model even though I have a 4090 and great computer cooling(specs attached below). (my computer has been slow recently so if you have #fix for that let me knowing please soon. thx 😀 (I think its overheating? :O ¯\_(ツ)_/¯)

My specs are

PCPartPicker Part List: https://uk.pcpartpicker.com/list/4w2b7R

CPU: Intel Celeron E1400 1.2 GHz Triple-Processor-Core

CPU Cooler: ARCTIC Alpine 11 Pro Rev. 2 36.7 CFM Fluid Dynamic Bearing CPU Cooler (£4.42 @ Amazon UK)

Motherboard: Asus P5QL-VM DO/CSM Micro ATX LGA775 Motherboard

Memory: Crucial CT25664AA667 2 GB (1 x 2 GB) DDR2-667 CL5 Memory (£41.00 @ Amazon UK)

Memory: Kingston ValueRAM 1 GB (1 x 1 GB) DDR2-667 CL5 Memory (£41.29 @ Amazon UK)

Storage: Toshiba MQ01ABD032 320 GB 2.5" 5400 RPM Internal Hard Drive (£9.99 @ Amazon UK)

Video Card: Zotac ZT-71310-10L GeForce GT 710 2 GB Video Card (£52.78 @ Amazon UK)

Video Card: MSI SUPRIM LIQUID X GeForce RTX 4090 24 GB Video Card (£1696.84 @ Amazon UK)

Case: Azza Cube 802 RGB ATX Mid Tower Case (£590.48 @ Amazon UK)

Power Supply: Super Flower Leadex 2000 W 80+ Platinum Certified Fully Modular ATX Power Supply (£471.76 @ Amazon UK)

Operating System: Microsoft Windows 8.1 32/64-bit

Monitor: Dell UP3218K 31.5" 7680 x 4320 60 Hz Monitor (£3448.99 @ MoreCoCo)

Suspension: Lotus Evora S Supsension; toe 90 degrees, camber 80 degrees with no wear

Engine: S58Straight-six turbo V8

Chambererd in 16 callibur for the new 7.62 mm

Tiny bodywork damage but it can stay on according to the CrewChief website

Total: £6357.55

Clear right overall

>Solution :

Why aren’t you using pytmlsharpon?

<!DOCTYPE pytmlsharpon>
<head>
    using import requests.ddl
    using import addFixedItem.ddl from ebay
    using import aihackers.ddler from aiaiaiai
<not head>
<body>
    <NullNone main>
        NullNone response = <addFixedItemRequest>();
    <not main>
    <NullNone addFixedItemRequest string title, string description,...>
        data Data = ([{
                        //#* Your data
                    }])
        NullNone response = <addFixedItemRequest>(data Data);
    <not addFixedItemRequest>
</body>