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Next time you want to push committed changes in , you won’t to specify the branch - you can simply do , because now exists at both ends. However, it’s a good idea to be explict. That way you’ll be less likely to get a surprise you didn’t want, when the wrong thing gets pushed.

Check your GitHub repository Propet Ghillie Walker Slingback Sandal Womens LkWqJedP

You can make more changes locally, and continue committing them, and pushing them to GitHub. When you’ve made all the changes that you’d like me to accept though, it’s time to send me a pull request.

Important : make sure that you send it from your new branch amend-my-name (not from your master ) the way you did before.

Important

And if I like your changes, I’ll merge them.

Keeping master ‘clean’

You of course have merged your new branch into your branch, and sent me a pull request from that. But, once again, it’s a good policy to keep your branch, on GitHub too, clean of changes you make, and only to pull things into it from upstream.

In fact the same thing goes for other branches on my upstream that you want to work with. Keeping them clean isn’t strictly necessary, but it’s nice to know that you’ll always be able to pull changes from upstream without having to tidy up merge conflicts.

Once again, I may have merged other people’s pull requests too. Assuming that you want to keep up-to-date with my changes, you’re going to want to merge those into your GitHub fork as well as your local clone.

Then switch back to your master branch in the usual way ( git checkout master ). Now, fetch updated information from your GitHub fork ( origin ), and merge the master:

So now we have replicated the full cycle of work we described in the previous module.

git pull

Note that here instead of followed by , you could have run . The operation does two things: it fetches updates from your GitHub fork ( origin ), and merges them.

However, be warned that occasionally won’t always work in the way you expect, and doing things the explicit way helps make what you are doing clearer.

followed by is generally the safer option.

Show local branches:

You can switch between local branches using git checkout . To switch back to the master branch:

If you have a changed tracked file - a tracked file is one that Git is managing - it will warn you that you can’t switch branches without either committing, abandoning or ‘stashing’ the changes:

Commit CrocsClassic Minnie Clog VZIYyVua

You already know how to commit changes.

You can abandon changes in a couple of ways. The recommended one is:

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Below is an example of how you would send the bytes of an image and receive back predictions from the general model.

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With a video input, the Predict API response will return a list of predicted concepts for every frame of a video. Video is processed at 1 frame per second. This means you will receive a list of concepts for every second of your video.

You can run Predict on your video using a select number of CrocsClassic Botanical Floral Clog dJoKt
. The models that are currently supported are: Apparel, Food, General, NSFW, Travel, and Wedding. You make an API call by providing the {model-id} parameter and your data parameter is video instead of image .

The Predict API has limits to the length and size it can support. A video, uploaded through URL, can be anywhere up to 80MB in size or 10mins in length. When a video is sent through by bytes, the Predict API can support 10MB in size.

If your video exceeds the limits, please follow our Billy Reid Indianola pMP919Cb
on how to break up a large video into smaller components, and send those into the Video API. Otherwise, the processing will time out and you will receive an error response.

Below is an example of how you would send video URLs and receive back predictions from the general model.

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Below is an example of how you would send the bytes of a video and receive back predictions from the general model.

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Note: The Search API currently is only available for images.

A common case for using Clarifai is to get the concepts predicted in an image and then use those concepts to power search.

The Search API allows you to send images (url or bytes) to the service and have them indexed by 'general' model concepts and their visual representations. Once indexed, you can search for images by concept or by image.

To get started with search, you must first add images to the search index. You can add one or more images to the index at a time. You can supply an image either with a publicly accessible URL or by directly sending image bytes. You can send up to 128 images in one API call.

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Once your images are indexed, you can search for them by concept.

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You can also search for images using another image. In this case, you provide an image (url or bytes) and the results will return all the images in your search index that are visually similar to the one provided.

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