Hello. There is anyway that I can crop a defined area in contours ? Iâm trying to crop a license car plate, but all algorithms that I tried work sometimes cropping exactly area of license car, sometimes contours find the right rectangle but it crops the wrong one, if I have x and y approximately could I do anything better ? Thanks all
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Using the above code on the notebook, I created a folder “df” and saved a data frame “Sample” into CSV. It is important to use coalesce(1) since it saves the data frame as a whole. At the end of this article, I will also demonstrate what happens when you don’t include coalesce(1) in the code.
Once you convert your data frame into CSV, go to your FileStore. You will see the folder and files you create. The “part-00000” is the CSV file I had to download on my local computer. I copied the path after /FileStore/ for step 3.
3. Download the CSV file on your local computer
In order to download the CSV file located in DBFS FileStore on your local computer, you will have to change the highlighted URL to the following:
As you noticed, the CSV path in bold (df/Sample.csv/part-00000-tid-8365188928461432060–63d7293d-3b02–43ff-b461-edd732f9e06e-4704-c000.csv) is from step 2. The number (3847738880082577) is from the original URL.
Export data from a table to CSV file using the \copy command
In case you have the access to a remote PostgreSQL database server, but you don’t have sufficient privileges to write to a file on it, you can use the PostgreSQL built-in command \copy.
The \copy command basically runs the COPY statement above. However, instead of server writing the CSV file, psql writes the CSV file, transfers data from the server to your local file system. To use \copy command, you just need to have sufficient privileges to your local machine. It does not require PostgreSQL superuser privileges.
For example, if you want to export all data of the persons table into persons_client.csv file, you can execute the \copy command from the psql client as follows:
\copy (SELECT * FROM persons) to'C:\tmp\persons_client.csv'with csv
The DENSE_RANK() ranking window function is similar to the RANK() function by generating a unique rank number for each distinct row within the partition according to a specified column value, starting at 1 for the first row in each partition, ranking the rows with equal values with the same rank number, except that it does not skip any rank, leaving no gaps between the ranks.
If we rewrite the previous ranking query to use the DENSE_RANK() ranking function:
Again, modify the previous query by including the PARTITION BY clause to have more than one partition, as shown in the T-SQL query below:
SELECT *, DENSE_RANK() OVER(PARTITION BY Student_Score ORDER BY Student_Score) AS RowNumberRank
The ranking values will have no meaning, where all the rows will be ranked with the value 1, due to assigning the duplicate values to the same ranking value and resetting the rank starting id when processing a new partition, as shown below:
The NTILE(N) ranking window function is used to distribute the rows in the rows set into a specified number of groups, providing each row in the row set with a unique group number, starting with the number 1 that shows the group this row belongs to, where N is a positive number, which defines the number of groups you need to distribute the rows set into.
In other words, if you need to divide specific data rows of the table into 3 groups, based on particular column values, the NTILE(3) ranking window function will help you to achieve this easily.
The number of rows in each group can be calculated by dividing the number of rows into the required number of groups. If we modify the previous ranking query to use NTILE(4) ranking window function to rank seven table rows into four groups as the T-SQL query below:
SELECT *, NTILE(4) OVER( ORDER BY Student_Score) AS NTILERank
The number of rows should be (7/4=1.75) rows into each group. Using the NTILE() function, SQL Server Engine will assign 2 rows to the first three groups and one row to the last group, in order to have all the rows included in the groups, as shown in the result set below:
Modifying the previous query by including the PARTITION BY clause to have more than one partition, as shown in the T-SQL query below:
SELECT *, NTILE(4) OVER(PARTITION BY Student_Score ORDER BY Student_Score) AS RowNumberRank
The rows will be distributed into four groups on each partition. For example, the first two rows with Student_Score equal to 770 will be in the same partition, and will be distributed within the groups ranking each one with a unique number, as shown in the result set below: