}

  public void testWithoutParameters() {
    assertSame(MediaType.parse("image/gif"), MediaType.parse("image/gif").withoutParameters());
    assertEquals(
        MediaType.parse("image/gif"), MediaType.parse("image/gif; foo=bar").withoutParameters());
  }

  public void testWithParameters() {
    assertEquals(
        MediaType.parse("text/plain; a=1; a=2; b=3"),

pkg image/color, var CMYKModel Model
pkg image/gif, const DisposalBackground = 2
pkg image/gif, const DisposalBackground ideal-int
pkg image/gif, const DisposalNone = 1
pkg image/gif, const DisposalNone ideal-int
pkg image/gif, const DisposalPrevious = 3
pkg image/gif, const DisposalPrevious ideal-int
pkg image/gif, type GIF struct, BackgroundIndex uint8
pkg image/gif, type GIF struct, Config image.Config

Using the below example document:
<img width="85%" src="https://bradley.codes/static/img/jstream-levels.gif" alt="jstream"/>

we can choose to extract and act only the objects within the top-level array:
```go
f, _ := os.Open("input.json")
decoder := jstream.NewDecoder(f, 1) // extract JSON values at a depth level of 1

            });
            task.from(extension.getCssFiles(), sub -> sub.into("css"));
            task.from(extension.getUserManual().getRoot().dir("img"), sub -> {
                sub.include("**/*.png", "**/*.gif", "**/*.jpg", "**/*.svg");
                sub.into("img");
            });
            task.from(extension.getUserManual().getResources());

            task.from(generateDocinfo);

        final String mimeType = responseData.getMimeType();
        if (mimeType == null) {
            return true;
        }

        return switch (mimeType) {
        case "image/png", "image/gif", "image/jpeg", "image/bmp" -> true;
        default -> false;
        };
    }

    protected Result saveImage(final ImageInputStream input, final File outputFile) throws IOException {

		<postConstruct name="addCondition">
			<arg>"mimetype"</arg>
			<arg>"image/x-ms-bmp"
			</arg>
		</postConstruct>
		<postConstruct name="addCondition">
			<arg>"mimetype"</arg>
			<arg>"image/gif"
			</arg>
		</postConstruct>
		<postConstruct name="addCondition">
			<arg>"mimetype"</arg>
			<arg>"image/png"
			</arg>
		</postConstruct>
		<postConstruct name="addCondition">

      }
      imgData = null;
    });
    imgData.src = url;
  };

  $("img.thumbnail").each(function() {
    $(this).css(
      "background-image",
      'url("' + contextPath + '/images/loading.gif")'
    );
    loadImage(this, $(this).attr("data-src"), IMG_LOADING_MAX);
  });
  
  var clipboard = new ClipboardJS(".url-copy");
  clipboard.on("success", function(e) {

  }

  @Test fun testValidParse() {
    assertMediaType("text/plain")
    assertMediaType("application/atom+xml; charset=utf-8")
    assertMediaType("application/atom+xml; a=1; a=2; b=3")
    assertMediaType("image/gif; foo=bar")
    assertMediaType("text/plain; a=1")
    assertMediaType("text/plain; a=1; a=2; b=3")
    assertMediaType("text/plain; charset=utf-16")
    assertMediaType("text/plain; \t \n \r a=b")

c.imageRatioNotAccepted;return!1},a.formUtils.addAsyncValidator({name:"dimension",validatorFunction:function(b,d,e,g,h){if(c){var i=e.get(0).files||[],j=this;e.attr("data-validation").indexOf("mime")===-1?(alert("You should validate file type being jpg, gif or png on input "+e[0].name),b(!1)):i.length>1?(alert("Validating image dimensions does not support inputs allowing multiple files"),b(!1)):0===i.length?b(!0):f(i[0],function(c){var d=!1;e.valAttr("dimension")&&(d=a.formUtils.checkImageDimension(c,...

have different security properties and provide different levels of confidence
when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could