Deleted vendor folder

1 files changed, 0 insertions, 129 deletions

diff --git a/vendor/exr/examples/8_read_raw_blocks.rs b/vendor/exr/examples/8_read_raw_blocks.rs
deleted file mode 100644
index 4864c98..0000000
--- a/vendor/exr/examples/8_read_raw_blocks.rs
+++ /dev/null
@@ -1,129 +0,0 @@
-
-extern crate rand;
-extern crate half;
-
-use std::io::{BufReader};
-use std::fs::File;
-use exr::block::reader::ChunksReader;
-
-// exr imports
-extern crate exr;
-
-
-/// Collects the average pixel value for each channel.
-/// Does not load the whole image into memory at once: only processes the image block by block.
-/// On my machine, this program analyzes a 3GB file while only allocating 1.1MB.
-fn main() {
-    use exr::prelude::*;
-
-    let file = BufReader::new(
-        File::open("3GB.exr")
-            .expect("run example `7_write_raw_blocks` to generate this image file")
-    );
-
-
-    // -- the following structs will hold the collected data from the image --
-
-    /// Collect averages for each layer in the image
-    #[derive(Debug)]
-    struct Layer {
-        #[allow(unused)] // note: is used in Debug impl
-        layer_name: Option<Text>,
-
-        data_window: IntegerBounds,
-
-        /// Collect one average float per channel in the layer
-        channels: Vec<Channel>,
-    }
-
-    /// A single channel in the layer, holds a single average value
-    #[derive(Debug)]
-    struct Channel {
-        #[allow(unused)] // note: is used in Debug impl
-        channel_name: Text,
-
-        sample_type: SampleType, // f32, u32, or f16
-        average: f32,
-    }
-
-    let start_time = ::std::time::Instant::now();
-
-
-    // -- read the file, summing up the average pixel values --
-
-    // start reading the file, extracting the meta data of the image
-    let reader = exr::block::read(file, true).unwrap();
-
-    // print progress only if it advances more than 1%
-    let mut current_progress_percentage = 0;
-
-    // create the empty data structure that will collect the analyzed results,
-    // based on the extracted meta data of the file
-    let mut averages = reader.headers().iter()
-        // create a layer for each header in the file
-        .map(|header| Layer {
-            layer_name: header.own_attributes.layer_name.clone(),
-            data_window: header.data_window(),
-
-            // create a averaging channel for each channel in the file
-            channels: header.channels.list.iter()
-                .map(|channel| Channel {
-                    channel_name: channel.name.clone(),
-                    sample_type: channel.sample_type,
-                    average: 0.0
-                })
-                .collect()
-        })
-        .collect::<Vec<_>>();
-
-    // create a reader that loads only relevant chunks from the file, and also prints something on progress
-    let reader = reader
-
-        // do not worry about multi-resolution levels or deep data
-        .filter_chunks(true, |meta_data, tile, block| {
-            let header = &meta_data.headers[block.layer];
-            !header.deep && tile.is_largest_resolution_level()
-        }).unwrap()
-
-        .on_progress(|progress|{
-            let new_progress = (progress * 100.0) as usize;
-            if new_progress != current_progress_percentage {
-                current_progress_percentage = new_progress;
-                println!("progress: {}%", current_progress_percentage)
-            }
-        });
-
-    // read all pixel blocks from the image, decompressing in parallel
-    reader.decompress_parallel(true, |meta_data, block|{
-        let header = &meta_data.headers[block.index.layer];
-
-        // collect all pixel values from the pixel block
-        for line in block.lines(&header.channels) {
-            let layer = &mut averages[line.location.layer];
-            let channel = &mut layer.channels[line.location.channel];
-            let channel_sample_count = layer.data_window.size.area() as f32;
-
-            // now sum the average based on the values in this line section of pixels
-            match channel.sample_type {
-                SampleType::F16 => for value in line.read_samples::<f16>() {
-                    channel.average += value?.to_f32() / channel_sample_count;
-                },
-
-                SampleType::F32 => for value in line.read_samples::<f32>() {
-                    channel.average += value? / channel_sample_count;
-                },
-
-                SampleType::U32 => for value in line.read_samples::<u32>() {
-                    channel.average += (value? as f32) / channel_sample_count;
-                },
-            }
-        }
-
-        Ok(())
-    }).unwrap();
-
-    println!("average values: {:#?}", averages);
-
-    // warning: highly unscientific benchmarks ahead!
-    println!("\nprocessed file in {:?}s", start_time.elapsed().as_secs_f32());
-}
\ No newline at end of file