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Follow step-by-step instructions to create a detail gallery in a canvas app for managing fictitious data in the Northwind Traders database. This topic is part of a series that explains how to build a business app on relational data in Microsoft Dataverse. For best results, explore these topics in this sequence:

Before you start this topic, you must install the database as described earlier in this topic. You must then either create the order gallery and the summary form or open the Northwind Orders (Canvas) - Begin Part 3 app, which already contains that gallery and that form.

You"ve just linked the two galleries. When the user selects an order in the order gallery, that selection identifies a record in the Orders table. If that order contains one or more line items, the record in the Orders table is linked to one or more records in the Order details table, and data from those records appears in the detail gallery. This behavior reflects the one-to-many relationship that was created for you between the Orders and Order Details tables. The formula that you specified "walks" that relationship by using dot notation:

In any gallery, you can show data but you can"t update it or add records. Under the detail gallery, you"ll add an area where the user can configure a record in the Order Details table and insert that record into an order.

In the Properties tab for the combo box, select Edit (next to Fields) to open the Data pane. Ensure that the Primary text and SearchField are set to nwind_productname.

You can build formulas that use data from any column (in the Order Products table) for whatever product the app user selects in the combo box that shows products. When the user selects a record in the Order Products table, not only does the product’s name appear in that combo box but also the product’s unit price appears in a label. Each lookup value in a canvas app references an entire record, not just a primary key.

The Refresh function ensures that the Orders table reflects the record that you’ve just added to the Order Details table. The Reset function clears the product, quantity, and unit-price data so that the user can more easily create another order detail for the same order.

This series of topics has been a quick walkthrough of using Dataverse relationships and choices in a canvas app for educational purposes. Before you release any app to production, you should consider field validation, error handling, and many other factors.

LED video wall solution with advanced video wall processing, off-board electronics, front serviceable cabinets and outstanding image quality available in 0.9mm pixel pitch

a line of extreme and ultra-narrow bezel LCD displays that provides a video wall solution for demanding requirements of 24x7 mission-critical applications and high ambient light environments

List Price is Lenovo’s estimate of product value based on the industry data, including the prices at which first and third-party retailers and etailers have offered or valued the same or comparable products. Third-party reseller data may not be based on actual sales.

Estimated value is Lenovo’s estimate of product value based on industry data, including the prices at which Lenovo and/or third-party retailers and e-tailers have offered or valued the same or comparable products. Third-party data may not be based on actual sales.

The LED-Panel V5 is one of the market’s most popular timing measurement devices for determining all the crucial timing values for digital cameras. We offer variations with different peak wavelengths, viewing angles, and versions that support near VIS-IR testing.

The latest version has a few notable features, including the ability to dim the LED array that greatly improves the use of the device under low-light conditions. Other parameters, including rolling shutter, shutter lag, and bright-light conditions, have improved accuracy, and frame rate has also expanded its measurement range. Finally, the USB interface now supports the entire speed range of the LED-Panel.

The LED-Panel uses an array of LEDs that offer various illumination modes and frequencies depending on the measurement parameters. This device meets all the requirements outlined in the timing measurement standard ISO 15781. The standard describes different timing measurements such as shooting time lag, negative shutter release time lag, shutter release time lag, shooting rate, and start-up time.

The LED-Panel can be easily integrated into the testing environment and combined with the iQ-Trigger and iQ-AF Box to create a complete timing measurement solution for digital camera systems.

The LED-Panel is equipped with user-friendly control software with a USB interface and includes a command-line interface. It can also be controlled using the manual controls on the device itself. Software features include:

We offer two versions of the standard LED-Panel. The first has a peak wavelength of 630 nm (red light) and a viewing angle of 100°. The second version has a peak wavelength of 525 nm (green light) and a viewing angle of 50°.

We also offer two versions of the LED-Panel IR. The first with a peak wavelength of 850 nm (NIR) and a viewing angle of 80°, the second with a peak wavelength of 940 nm (NIR) and a viewing angle of 90°.

If you have a particular requirement, we have a C++ application program interface (API) available. When using the LED-Panel API, you can modify the start and stop timing of the device, change measurement modes, and incorporate other products (i.e., iQ-Trigger) for use with the LED-Panel, among others.

With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. When using Rekognition Custom Labels, there are two types of costs.

Training HoursThere is a cost for each hour of training required to build a custom model with Amazon Rekognition Custom Labels. Amazon Rekognition Custom Labels may run multiple compute resources in parallel to train your model more quickly. This means that the number of hours billed may be more than the number of actual elapsed hours it takes to train the model. The number of training hours needed to train your model depends on many factors such as number of images and number of labels in the training set, and types of machine learning algorithms used to train your model. We have typically seen that 90% of models need less than 24 training hours to train. Models that take more than 72 training hours will be automatically terminated. You will not be charged if your training is automatically terminated.

There is a cost for each hour your trained custom model is available to process images. The number of images you can process in a single hour depends on many factors, such as the size of the images processed and the complexity of the custom model. With Amazon Rekognition Custom Labels, you can run multiple compute resources in parallel to process your images more quickly. This means that the number of hours billed may be more than the actual elapsed hours it takes to run your trained custom model.

For example, let’s assume you started your inference with your custom model at 2:00pm and ended at 5:00pm, and you chose to provision two resources in parallel to process your images. Your total inference hours billed would be 6 hours (3 hours elapsed time x 2 resources).

If you expect to process images in batches (e.g. once a day or week, or at scheduled times during the day), you should provision your custom model at scheduled times, process all your images, and then deprovision your resources. If you do not deprovision your resources, you will continue to be charged even if no images are processed.