web yönlendirmesini kontrol et url durum kodu denetleyicisi

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Ham HTML kodu
301 Moved Permanently - rf100.com
HTTP Status: 301
User-Agent: Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; [email protected])
Content-Type: text/html; charset=utf-8
Location: https://www.rf100.org
X-Redirector-Version: d6fd824
Date: Wed, 28 May 2025 01:39:09 GMT
Content-Length: 56
Connection: close
server: GitHub.com
content-type: text/html; charset=utf-8
last-modified: Fri, 09 Feb 2024 23:10:23 GMT
access-control-allow-origin: *
etag: "65c6b0df-4fe9"
expires: Wed, 28 May 2025 01:49:09 GMT
cache-control: max-age=600
x-proxy-cache: MISS
x-github-request-id: C65E:3910D2:93181A:94632E:6836693C
accept-ranges: bytes
age: 0
date: Wed, 28 May 2025 01:39:09 GMT
via: 1.1 varnish
x-served-by: cache-hel1410024-HEL
x-cache: MISS
x-cache-hits: 0
x-timer: S1748396349.280016,VS0,VE139
vary: Accept-Encoding
x-fastly-request-id: 9f91abc2af05981a80d1936c2f876c0d109f039d
content-length: 20457

HTTP Kodu 301 Kalıcı Olarak Taşındı

301 Moved Permanently, istenen kaynağın kalıcı olarak yeni bir URL'ye taşındığı anlamına gelir. Gelecekteki tüm istekler yeni adresi kullanmalıdır.

Kod 301 ne zaman kullanılır?

  • Bir web sitesi alan adını değiştirirken
  • URL yapılarını değiştirirken
  • SEO için yönlendirmeleri ayarlarken

Kod 301 kullanıcı için ne anlama geliyor?

Tarayıcı kullanıcıyı otomatik olarak yeni adrese yönlendirecek ve arama motorları dizinlerini güncelleyecektir.

GET / HTTP/1.1
Host: rf100.com
Accept: */*
User-Agent: Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; [email protected])

<!DOCTYPE html>
<!--  Last Published: Wed Nov 23 2022 08:52:15 GMT+0000 (Coordinated Universal Time)  -->
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    <title>Roboflow 100: A New Object Detection Benchmark</title>
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    <meta
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      content="Advancing the state-of-the-art in object recognition with a new way to benchmark computer vision models across domains and task targets."
    />

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      type="text/javascript"
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      gtag("js", new Date());

      gtag("config", "G-SJD0NKSWQ1");
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    <style>
      .icon_close {
        -webkit-user-select: none; /* Chrome all / Safari all */
        -moz-user-select: none; /* Firefox all */
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        user-select: none;
      }
      hr {
        border-color: #ffc300;
        margin-top: 32px;
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        border-style: solid;
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    </style>
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  </head>
  <body>
    <div class="header--secondary">
      <div class="nav__default">
        <div class="nav__main">
          <a href="index.html" class="nav__logo__link w-inline-block"
            ><img
              src="static/images/logo-4x.png"
              loading="lazy"
              width="480"
              height="192"
              alt=""
              class="nav__logo"
          /></a>
          <div class="text-block-25">100</div>
        </div>
      </div>
    </div>
    <div class="section_wrap wf-section">
      <div class="w-container">
        <h1>Roboflow 100: A New Object Detection Benchmark<br /></h1>
        <div class="subhead">
          Advancing the state-of-the-art in object recognition with a new way to benchmark computer vision models across domains and task targets. Introduced November 2022, presented at <a href="https://computer-vision-in-the-wild.github.io/cvpr-2023/">CVPR in June 2023</a>.
        </div>
        <img
          src="static/images/roboflow100mosaic.jpg"
          loading="lazy"
          srcset="
            static/images/roboflow100mosaic-p-500.jpg  500w,
            static/images/roboflow100mosaic-p-800.jpg  800w,
            static/images/roboflow100mosaic.jpg       1080w,
            static/images/roboflow100mosaic.jpg       1600w
          "
          sizes="(max-width: 479px) 93vw, (max-width: 767px) 94vw, (max-width: 991px) 92vw, 94vw"
          alt=""
          class="cover"
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        <div class="w-layout-grid layout_left_sidebar rf100">
          <div
            id="w-node-_321897c8-728e-2bf4-585c-ad79172fa307-b80115c2"
            class="left_sidebar"
          >
            <div class="profile_card maxheight">
              <img
                src="static/images/rf100paper-icon4.png"
                loading="lazy"
                alt=""
                class="image-3"
              />
              <div>
                <div class="linklist-wrap">
                  <div class="linklist-head">
                    <strong>Datasets in Roboflow 100</strong>
                  </div>
                  <div class="linklist">
                    <a href="https://universe.roboflow.com/roboflow-100"
                      ><span class="fa_icon sq"></span> Explore datasets</a
                    >
                  </div>
                  <div class="linklist">
                    <a href="https://www.rf100.org/visual.html"
                      ><span class="fa_icon sq"></span> Explore dataset
                      cloud</a
                    >
                  </div>
                </div>
                <div class="linklist-wrap">
                  <div class="linklist-head"><strong>Paper</strong></div>
                  <div class="linklist">
                    <a href="https://arxiv.org/abs/2211.13523"
                      ><span class="fa_icon sq"></span> Download paper</a
                    >
                  </div>
                </div>
                <div class="linklist-wrap">
                  <div class="linklist-head"><strong>Evaluate</strong></div>
                  <div class="linklist">
                    <a
                      href="https://github.com/roboflow/roboflow-100-benchmark"
                      ><span class="fa_icon sq"></span> Github</a
                    >
                  </div>
                  <div class="linklist">
                    <a
                      href="https://paperswithcode.com/dataset/rf100"
                      ><span class="fa_icon sq"></span> Papers with Code</a
                    >
                  </div>
                </div>
              </div>
            </div>
          </div>
          <div
            id="w-node-_321897c8-728e-2bf4-585c-ad79172fa32f-b80115c2"
            class="right_content centeralign"
          >
            <h2 id="w-node-_321897c8-728e-2bf4-585c-ad79172fa330-b80115c2">
              What is the Roboflow 100?
            </h2>
            <p class="subtext">
              Roboflow 100 introduces domain-specific benchmarks beyond common
              objects in context to identify how models adapt to diverse
              problems in healthcare, aerial imagery, video games, and more.
            </p>
            <p>
              Object detection benchmarks have traditionally focused on a single
              dataset for fine-tuning and evaluation such as Microsoft COCO and
              Pascal VOC. While semantically diverse within their domain, these
              benchmarks focus on optimizing a single metric for a single
              dataset, which does not show the degree of generalization learned
              by the model.
            </p>
            <p>
              In this paper we introduce the Roboflow 100 object detection
              benchmark consisting of 100 projects that span a wide array of
              imagery domains and task targets. We derived our benchmark
              selection from over 90000 public datasets, 60 million public
              images that are actively being worked on in the open on Roboflow.
            </p>
            <iframe
              height="400"
              width="100%"
              src="https://www.youtube.com/embed/i8amBaHrhqY"
            >
            </iframe>
          </div>
        </div>
        <div class="container-6">
          <div class="features-wrapper-2">
            <div class="features-block-2">
              <div class="features-title-2">100</div>
              <div>Separate datasets</div>
            </div>
            <div class="features-block-2">
              <div class="features-title-2">7</div>
              <div>Imagery domains</div>
            </div>
            <div class="features-block-2">
              <div class="features-title-2">224,714</div>
              <div>Images</div>
            </div>
            <div class="features-block-2">
              <div class="features-title-2">
                829<span class="features-title-small-2"></span>
              </div>
              <div>Class labels</div>
            </div>
            <div class="features-block-2">
              <div class="features-title-2">
                11,170<span class="features-title-small-2"></span>
              </div>
              <div>Labeling hours</div>
            </div>
          </div>
        </div>
      </div>
    </div>
    <div style="padding-left: 2rem; margin-right: 2rem">
      <iframe style="width: 100%; height: 800px" src="visual.html"></iframe>
    </div>
    <div class="section--default--gray rf100 wf-section">
      <div class="w-container">
        <div class="w-layout-grid grid-2">
          <div
            id="w-node-_69f5695e-c4a0-3631-d66c-775dcdd72030-b80115c2"
            class="div-block-6"
          >
            <h3
              id="w-node-_69f5695e-c4a0-3631-d66c-775dcdd72033-b80115c2"
              class="gray"
            >
              Inspired by
            </h3>
            <p>
              The assembly of the Roboflow 100 benchmark was inspired by the
              research community naturally using Roboflow datasets to test model
              generalizability in
              <a
                href="https://www.microsoft.com/en-us/research/project/projectflorence/"
                >Microsoft&#x27;s Florence</a
              >
              and <a href="https://github.com/microsoft/GLIP">GLIP</a>.
            </p>
            <h3 class="gray">How to use</h3>
            <p>
              Details can be found on the
              <a href="https://github.com/roboflow-ai/roboflow-100-benchmark"
                >Roboflow 100 GitHub page</a
              >.
            </p>
            <h3 class="gray">Organizers</h3>
            <p>
              <a href="https://www.linkedin.com/in/floriana-ciaglia-53074b187/"
                >Floriana Ciaglia</a
              >,
              <a
                href="https://www.linkedin.com/in/francesco-saverio-zuppichini-94659a150/"
                >Francesco Saverio Zuppichini</a
              >,
              <a href="https://www.linkedin.com/in/paul-guerrie-7681b561/"
                >Paul Guerrie</a
              >,
              <a href="https://www.linkedin.com/in/mark-mcquade/">
                Mark McQuade</a
              >, and
              <a href="https://www.linkedin.com/in/jacob-solawetz-a92832a7/"
                >Jacob Solawetz</a
              ><br />
            </p>
            <h3 class="gray">Made by</h3>
            <p>
              <a
                href="https://github.com/roboflow-ai/roboflow-100-benchmark#credits"
                >The Roboflow Community</a
              >
            </p>
            <h3 class="gray">Sponsored by</h3>
            <p><a href="https://intel.com">Intel</a><br /></p>
          </div>
          <div
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              href="https://blog.roboflow.com/roboflow-100/"
              class="card-link-wrap w-inline-block"
            >
              <div
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                    srcset="
                      static/images/roboflow100mosaic-p-500.jpg  500w,
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                    "
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                    alt=""
                    class="cards-image blog"
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                </div>
                <div class="card-text">
                  <h4 class="card-heading">Announcing Roboflow 100 📸</h4>
                  <div class="author">
                    <strong>Francesco Zuppichini</strong>
                  </div>
                  <p class="card-paragraph">
                    Roboflow 100 (RF100) is a crowdsourced object detection
                    benchmark. In this article, the data collection method and
                    what&#x27;s in the dataset are discussed at a high level.
                  </p>
                </div>
              </div>
            </a>
          </div>
        </div>
      </div>
    </div>
    <section class="footer-rf100 wf-section">
      <div class="container-8">
        <div class="footer-bottom">
          <div class="footer-copyright">Roboflow 100</div>
          <div class="footer-legal-block">
            <a href="https://roboflow.com/terms" class="footer-legal-link"
              >Terms Of Use</a
            >
          </div>
        </div>
      </div>
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