diff --git a/Project.toml b/Project.toml
index 8811d26..b151df6 100644
--- a/Project.toml
+++ b/Project.toml
@@ -3,6 +3,16 @@ uuid = "308a64e0-2da8-4ffc-993f-c99ea7c8dc9b"
 authors = ["Wenbo Li <wenboli2016@gmail.com> and contributors"]
 version = "1.0.0-DEV"
 
+[deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DICOM = "a26e6606-dd52-5f6a-a97f-4f611373d757"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
+Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
+NIfTI = "a3a9e032-41b5-5fc4-967a-a6b7a19844d3"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+
 [compat]
 julia = "1"
 
diff --git a/README.md b/README.md
index 886a394..e69de29 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +0,0 @@
-# imageToolBox
-
-[![Build Status](https://github.com/Wenbo Li/imageToolBox.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/Wenbo Li/imageToolBox.jl/actions/workflows/CI.yml?query=branch%3Amain)
diff --git a/src/dicom_tools.jl b/src/dicom_tools.jl
new file mode 100644
index 0000000..91aad77
--- /dev/null
+++ b/src/dicom_tools.jl
@@ -0,0 +1,116 @@
+using DICOM, Statistics
+
+"""
+    This function reads the dicom file.
+    - input:
+        1. path to the dicom file
+    - output:
+        1. dcm_data
+        2. SID
+        3. V_P
+        4. image
+"""
+function read_dicom(path_to_file::String)
+    dcm_data = dcm_parse(path_to_file)
+    # image
+    image = dcm_data[(0x7fe0, 0x0010)]
+    # v_p
+    LorR = ""
+    try
+        LorR = uppercase(dcm_data[(0x0020,0x0062)])
+    catch e
+        println("---------Error---------")
+        println(e)
+        println(curr_path)
+        println("---------Error---------")
+    end
+    V_P = ""
+    try
+        V_P = uppercase(dcm_data[(0x0018,0x5101)])
+    catch e
+        println("---------Error---------")
+        println(e)
+        println(curr_path)
+        println("---------Error---------")
+    end
+    curr_key = LorR*" "*V_P
+    # SID
+    sid = [(0x0010, 0x0020)]
+    return dcm_data, sid, curr_key, image
+end
+
+"""
+    This function gets the number of patches needed for a iamge.
+    - input:
+        1. Matrix of Float32: the image
+        2. Matrix of Float32: the roi
+        3. Matrix of Float32: the binary mask representing the breast area.
+    - optional input:
+        1. Float64: `thd`. The threshold of percentage of the white area. Default = 0.35
+        2. Int: 'patch_size'. The size of each patch. Default = 256
+    - output:
+        1. int: Number of without-BAC patches.
+        2. int: Number of with-BAC patches.
+"""
+function get_num_of_patches(img::Matrix{Float32}, lbl::Matrix{Float32}, mask::Matrix{Float32}; thd = 0.35, patch_size = 256)
+    patch_size_half = round(Int, patch_size/2)
+    s = size(img)
+    x = ceil(Int, s[1]/patch_size) + floor(Int, (s[1]-patch_size_half)/patch_size)
+    y = ceil(Int, s[2]/patch_size) + floor(Int, (s[2]-patch_size_half)/patch_size)
+    ct_empty, ct_non_empty = 0, 0
+    for i = 1 : x-1
+        x_start = 1+(i-1)*patch_size_half
+        x_end = x_start+patch_size-1
+        for j = 1 : y-1
+            y_start = 1+(j-1)*patch_size_half
+            y_end = y_start+patch_size-1
+            # check if this is forgounrd
+            if mean(mask[x_start:x_end, y_start:y_end]) > thd
+                # check if contains BAC
+                if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+                    ct_non_empty += 1
+                else
+                    ct_empty += 1
+                end
+            end
+        end
+        # right col
+        y_start, y_end = s[2]-patch_size+1, s[2]
+        # check if this is forgounrd
+        if mean(mask[x_start:x_end, y_start:y_end]) > thd
+            # check if contains BAC
+            if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+                ct_non_empty += 1
+            else
+                ct_empty += 1
+            end
+        end
+    end
+    # last row
+    x_start, x_end = s[1]-patch_size+1, s[1]
+    for j = 1 : y-1
+        y_start = 1+(j-1)*patch_size_half
+        y_end = y_start+patch_size-1
+        # check if this is forgounrd
+        if mean(mask[x_start:x_end, y_start:y_end]) > thd
+            # check if contains BAC
+            if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+                ct_non_empty += 1
+            else
+                ct_empty += 1
+            end
+        end
+    end
+    # right col
+    y_start, y_end = s[2]-patch_size+1, s[2]
+    # check if this is forgounrd
+    if mean(mask[x_start:x_end, y_start:y_end]) > thd
+        # check if contains BAC
+        if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+            ct_non_empty += 1
+        else
+            ct_empty += 1
+        end
+    end
+    return ct_empty, ct_non_empty
+end
\ No newline at end of file
diff --git a/src/imageToolBox.jl b/src/imageToolBox.jl
index 943abfb..a70c278 100644
--- a/src/imageToolBox.jl
+++ b/src/imageToolBox.jl
@@ -1,5 +1,17 @@
 module imageToolBox
 
-# Write your package code here.
+using Pkg
+Pkg.activate("..")
+Pkg.instantiate()
 
-end
+include("dicom_tools.jl")
+include("nifty_tools.jl")
+include("png_tools.jl")
+include("other_tools.jl")
+
+export save_to_csv, get_last_edit_time, search_files_by_ext, search_files_by_name, binary_search_SID
+export zoom_pixel_values, copy_file, clean_directory, normalize_img
+export read_png, get_breast_mask
+export read_dicom, get_num_of_patches
+
+end
\ No newline at end of file
diff --git a/src/nifty_tools.jl b/src/nifty_tools.jl
new file mode 100644
index 0000000..e69de29
diff --git a/src/other_tools.jl b/src/other_tools.jl
new file mode 100644
index 0000000..5683c08
--- /dev/null
+++ b/src/other_tools.jl
@@ -0,0 +1,246 @@
+using CSV, DataFrames, Dates
+
+
+
+
+
+"""
+    This function saves data to local as csv file.
+    - input:
+      1. String: file_name
+      2. 1-D Array of Strings: column normalizes
+      3. 2-D Array: data
+"""
+function save_to_csv(column_names_, data::Matrix, csv_name::String)
+    column_names = vec(column_names_)
+    # Ensure the column names match the data dimensions
+    if size(data, 2) != length(column_names)
+        throw(ArgumentError("Mismatch between number of columns in data and provided column names"))
+    end
+
+    # Create a DataFrame from the data and column names
+    df = DataFrame(data, Symbol.(column_names))
+
+    # Save the DataFrame to a CSV file
+    CSV.write(csv_name, df)
+end
+
+"""
+    This function gets the last edit time of a file.
+    - input:
+        1. String: path to the file
+    - output:
+        1. Dates: the last edit time
+"""
+function get_last_edit_time(file_path::String)
+    try
+        # Get the file's stat information
+        file_stat = stat(file_path)
+        
+        # Extract the last modification time (mtime) in seconds since the epoch
+        last_edit_time_epoch = file_stat.mtime
+        
+        # Convert the epoch time to a more readable DateTime format
+        last_edit_time = Dates.unix2datetime(last_edit_time_epoch)
+        
+        return last_edit_time
+    catch e
+        println("An error occurred: ", e)
+        return nothing
+    end
+end
+
+"""
+    This function recursively look for all files in folders and subfolders.
+    - input:
+        1. String: root dir
+        2. String: extension of a file to search for. Note: input should be ".dcm" instead of "dcm".
+    - output:
+        1. Array: a list of found paths.
+"""
+function search_files_by_ext(root_dir, file_ext)
+
+	files=[]
+	
+	# collect curr folder info
+	sub_files, sub_dirs = [], []
+	for f in readdir(root_dir)
+		curr_path = joinpath(root_dir, f)
+
+		if isdir(curr_path)
+			push!(sub_dirs, curr_path)
+		else
+			push!(sub_files, curr_path)
+		end
+	end
+	dir_ct = size(sub_dirs)[1]
+	files_found = Array{Any}(undef, dir_ct)
+	
+	# folders: rec calls
+	Threads.@threads for i = 1 : dir_ct
+		files_found[i] = rec_search(sub_dirs[i], file_ext)
+	end
+	
+	# Append after multithreading to prevent data races
+	for i = 1 : dir_ct
+		append!(files, files_found[i])
+	end
+
+	# files: check if it's DICOM image
+	for f in sub_files
+		 _, f_ext = splitext(f)
+		if f_ext == file_ext
+			push!(files, f)
+		end
+	end
+	
+	return files
+end
+
+"""
+    This function recursively look for the target file.
+    - input:
+        1. String: root dir
+        2. String: file name of the target file
+    - output:
+        1. Array of String: path to the target file. "" if not found.
+"""
+function search_files_by_name(root_dir, file_name)
+	# collect curr folder info
+	sub_files, sub_dirs = [], []
+	for f in readdir(root_dir)
+		curr_path = joinpath(root_dir, f)
+
+		if isdir(curr_path)
+			push!(sub_dirs, curr_path)
+		else
+			push!(sub_files, curr_path)
+		end
+	end
+	dir_ct = size(sub_dirs)[1]
+	files_found = Array{Any}(undef, dir_ct)
+	
+	# folders: rec calls
+	Threads.@threads for i = 1 : dir_ct
+		files_found[i] = search_files_by_name(sub_dirs[i], file_name)
+	end
+
+    new_founds = Array{String, 1}(undef, 0)
+	# files: check if it's target_file
+	for f in sub_files
+		if rsplit(f, "/"; limit = 2)[2] == file_name
+            push!(new_founds, f)
+		end
+	end
+
+    rslt = Array{String, 1}(undef, 0)
+    # combine paths
+    for f in files_found
+        for ff in f
+            if ff != ""
+                push!(rslt, ff)
+            end
+        end
+    end
+    for ff in new_founds
+        if ff != ""
+            push!(rslt, ff)
+        end
+    end
+    return unique(rslt)
+end
+
+"""
+    This function looks for a target element in a array. The input array should be already sorted.
+    - input:
+        1. Array of T: list contains the target
+        2. T: the target
+    - output:
+        1. int: index of the target in SID list. -1 if not found.
+"""
+function binary_search_SID(SIDs, target)
+    low = 1
+    high = size(SIDs)[1]
+    
+    while low <= high
+        mid = div(low + high, 2)
+        
+        if SIDs[mid] == target
+            return mid
+        elseif SIDs[mid] < target
+            low = mid + 1
+        else
+            high = mid - 1
+        end
+    end
+    
+    return -1  # Return -1 if the target is not found
+end
+
+"""
+    This function zoom pixel values of a image to range of [0, 1].
+    - input:
+        1. Matrix: the input image
+    - output: 
+        1. Matrix: the zoomed image.
+"""
+function zoom_pixel_values(img)
+    a, b = minimum(img), maximum(img)
+    img_ = (img .- a) ./ (b - a)
+    return img_
+end
+
+"""
+    This function copys a file to a new path.
+    - input:
+        1. String: old path of the file
+        2. String: new path of the file
+"""
+function copy_file(old_path::String, new_path::String)
+    # Check if the old DICOM file exists
+    if !isfile(old_path)
+        println("Error: The file does not exist.")
+        return
+    end
+    
+    # Check if the new path directory exists, if not create it
+    new_dir = dirname(new_path)
+    if !isdir(new_dir)
+        # println("Creating new directory: ", new_dir)
+        mkpath(new_dir)
+    end
+    
+    # Copy the file
+    if isfile(new_path)
+        return
+    end
+    try
+        cp(old_path, new_path)
+    catch e
+        println("An error occurred while copying the file: ", e)
+    end
+end
+
+"""
+    This function deletes verything inside the dir.
+    - input:
+        1. String: dir to be cleaned.
+"""
+function clean_directory(directory::String)
+    for item in readdir(directory)
+        item_path = joinpath(directory, item)
+        rm(item_path, recursive=true)
+    end
+end
+
+"""
+    This function changes the image, making mean of all pixel values to 0, and std to 1
+"""
+function normalize_img(img)
+    m = maximum(img)
+    img = m .- img
+    a = mean(img)
+    s = std(img)
+    img = (img .- a) ./ s 
+    return img
+end
\ No newline at end of file
diff --git a/src/png_tools.jl b/src/png_tools.jl
new file mode 100644
index 0000000..610ded5
--- /dev/null
+++ b/src/png_tools.jl
@@ -0,0 +1,28 @@
+using Images
+
+"""
+    This function read a png file.
+    - input:
+        1. String: Path to the png file
+    - output:
+        1. Matrix{Float32}: the image
+"""
+function read_png(path_to_file::String)
+    _, f_ext = splitext(path_to_file)
+    if f_ext != ".png"
+        println("Error: not a png file.")
+    end
+    return Float32.(Images.load(path_to_file))
+end
+
+"""
+    This function find the breast area and create a mask.
+    - input:
+        1. Matrix{Float32}: the raw image.
+    - output:
+        1. Matrox{Float32}: the binary mask.
+"""
+function get_breast_mask(raw_img::Matrix{Float32})
+    mask = 1 .- round.(imageToolBox.zoom_pixel_values(raw_img))
+    return mask
+end
\ No newline at end of file
diff --git a/test/runtest.jl b/test/runtest.jl
new file mode 100644
index 0000000..caf606d
--- /dev/null
+++ b/test/runtest.jl
@@ -0,0 +1,18 @@
+using JuliaNiftyReg
+using Test
+
+@testset "other_tools.jl" begin
+    # Write your tests here.
+end
+
+@testset "dicom_tools.jl" begin
+    # Write your tests here.
+end
+
+@testset "nifty_tools.jl" begin
+    # Write your tests here.
+end
+
+@testset "png_tools.jl" begin
+    # Write your tests here.
+end
\ No newline at end of file
diff --git a/test/runtests.jl b/test/runtests.jl
deleted file mode 100644
index f7b6b09..0000000
--- a/test/runtests.jl
+++ /dev/null
@@ -1,6 +0,0 @@
-using imageToolBox
-using Test
-
-@testset "imageToolBox.jl" begin
-    # Write your tests here.
-end
diff --git a/testrun.ipynb b/testrun.ipynb
new file mode 100644
index 0000000..50d95ec
--- /dev/null
+++ b/testrun.ipynb
@@ -0,0 +1,718 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m\u001b[1m  Activating\u001b[22m\u001b[39m project at `~/Desktop/imageToolBox.jl/imageToolBox.jl`\n",
+      "\u001b[32m\u001b[1m   Resolving\u001b[22m\u001b[39m package versions...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m StatsAPI ───────────── v1.7.0\n",
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m PkgVersion ─────────── v0.3.3\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m ProgressMeter ──────── v1.9.0\n",
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m StaticArrayInterface ─ v1.4.1\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m JLD2 ───────────────── v0.4.34\n",
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m JLLWrappers ────────── v1.5.0\n",
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m StaticArrays ───────── v1.6.3\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m LogExpFunctions ────── v0.3.26\n",
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m CPUSummary ─────────── v0.2.4\n",
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m TiffImages ─────────── v0.6.5\n",
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m Rotations ──────────── v1.6.0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m\u001b[1m   Installed\u001b[22m\u001b[39m ColorSchemes ───────── v3.24.0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m\u001b[1m    Updating\u001b[22m\u001b[39m `~/Desktop/imageToolBox.jl/imageToolBox.jl/Project.toml`\n",
+      "  \u001b[90m[916415d5] \u001b[39m\u001b[92m+ Images v0.26.0\u001b[39m\n",
+      "\u001b[32m\u001b[1m    Updating\u001b[22m\u001b[39m `~/Desktop/imageToolBox.jl/imageToolBox.jl/Manifest.toml`\n",
+      "  \u001b[90m[621f4979] \u001b[39m\u001b[92m+ AbstractFFTs v1.5.0\u001b[39m\n",
+      "  \u001b[90m[79e6a3ab] \u001b[39m\u001b[92m+ Adapt v3.6.2\u001b[39m\n",
+      "  \u001b[90m[ec485272] \u001b[39m\u001b[92m+ ArnoldiMethod v0.2.0\u001b[39m\n",
+      "  \u001b[90m[4fba245c] \u001b[39m\u001b[92m+ ArrayInterface v7.4.11\u001b[39m\n",
+      "  \u001b[90m[30b0a656] \u001b[39m\u001b[92m+ ArrayInterfaceCore v0.1.29\u001b[39m\n",
+      "  \u001b[90m[13072b0f] \u001b[39m\u001b[92m+ AxisAlgorithms v1.0.1\u001b[39m\n",
+      "  \u001b[90m[39de3d68] \u001b[39m\u001b[92m+ AxisArrays v0.4.7\u001b[39m\n",
+      "  \u001b[90m[62783981] \u001b[39m\u001b[92m+ BitTwiddlingConvenienceFunctions v0.1.5\u001b[39m\n",
+      "  \u001b[90m[fa961155] \u001b[39m\u001b[92m+ CEnum v0.4.2\u001b[39m\n",
+      "  \u001b[90m[2a0fbf3d] \u001b[39m\u001b[92m+ CPUSummary v0.2.4\u001b[39m\n",
+      "  \u001b[90m[aafaddc9] \u001b[39m\u001b[92m+ CatIndices v0.2.2\u001b[39m\n",
+      "  \u001b[90m[d360d2e6] \u001b[39m\u001b[92m+ ChainRulesCore v1.16.0\u001b[39m\n",
+      "  \u001b[90m[fb6a15b2] \u001b[39m\u001b[92m+ CloseOpenIntervals v0.1.12\u001b[39m\n",
+      "  \u001b[90m[aaaa29a8] \u001b[39m\u001b[92m+ Clustering v0.15.4\u001b[39m\n",
+      "  \u001b[90m[35d6a980] \u001b[39m\u001b[92m+ ColorSchemes v3.24.0\u001b[39m\n",
+      "  \u001b[90m[3da002f7] \u001b[39m\u001b[92m+ ColorTypes v0.11.4\u001b[39m\n",
+      "  \u001b[90m[c3611d14] \u001b[39m\u001b[92m+ ColorVectorSpace v0.10.0\u001b[39m\n",
+      "  \u001b[90m[5ae59095] \u001b[39m\u001b[92m+ Colors v0.12.10\u001b[39m\n",
+      "  \u001b[90m[ed09eef8] \u001b[39m\u001b[92m+ ComputationalResources v0.3.2\u001b[39m\n",
+      "  \u001b[90m[150eb455] \u001b[39m\u001b[92m+ CoordinateTransformations v0.6.3\u001b[39m\n",
+      "  \u001b[90m[adafc99b] \u001b[39m\u001b[92m+ CpuId v0.3.1\u001b[39m\n",
+      "  \u001b[90m[dc8bdbbb] \u001b[39m\u001b[92m+ CustomUnitRanges v1.0.2\u001b[39m\n",
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+      "\u001b[33m⌅\u001b[39m \u001b[90m[f27b6e38] \u001b[39m\u001b[92m+ Polynomials v3.2.13\u001b[39m\n",
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+      "  \u001b[90m[699a6c99] \u001b[39m\u001b[92m+ SimpleTraits v0.9.4\u001b[39m\n",
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+      "  \u001b[90m[62fd8b95] \u001b[39m\u001b[92m+ TensorCore v0.1.1\u001b[39m\n",
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+      "  \u001b[90m[06e1c1a7] \u001b[39m\u001b[92m+ TiledIteration v0.5.0\u001b[39m\n",
+      "  \u001b[90m[3a884ed6] \u001b[39m\u001b[92m+ UnPack v1.0.2\u001b[39m\n",
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+      "  \u001b[90m[f5851436] \u001b[39m\u001b[92m+ FFTW_jll v3.3.10+0\u001b[39m\n",
+      "\u001b[33m⌅\u001b[39m \u001b[90m[c73af94c] \u001b[39m\u001b[92m+ ImageMagick_jll v6.9.10-12+3\u001b[39m\n",
+      "  \u001b[90m[905a6f67] \u001b[39m\u001b[92m+ Imath_jll v3.1.7+0\u001b[39m\n",
+      "  \u001b[90m[1d5cc7b8] \u001b[39m\u001b[92m+ IntelOpenMP_jll v2023.2.0+0\u001b[39m\n",
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+      "  \u001b[90m[88015f11] \u001b[39m\u001b[92m+ LERC_jll v3.0.0+1\u001b[39m\n",
+      "\u001b[33m⌅\u001b[39m \u001b[90m[89763e89] \u001b[39m\u001b[92m+ Libtiff_jll v4.4.0+0\u001b[39m\n",
+      "  \u001b[90m[856f044c] \u001b[39m\u001b[92m+ MKL_jll v2023.2.0+0\u001b[39m\n",
+      "  \u001b[90m[18a262bb] \u001b[39m\u001b[92m+ OpenEXR_jll v3.1.4+0\u001b[39m\n",
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+      "  \u001b[90m[b53b4c65] \u001b[39m\u001b[92m+ libpng_jll v1.6.38+0\u001b[39m\n",
+      "  \u001b[90m[075b6546] \u001b[39m\u001b[92m+ libsixel_jll v1.10.3+0\u001b[39m\n",
+      "  \u001b[90m[8ba89e20] \u001b[39m\u001b[92m+ Distributed\u001b[39m\n",
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+      "  \u001b[90m[1a1011a3] \u001b[39m\u001b[92m+ SharedArrays\u001b[39m\n",
+      "  \u001b[90m[4607b0f0] \u001b[39m\u001b[92m+ SuiteSparse\u001b[39m\n",
+      "  \u001b[90m[05823500] \u001b[39m\u001b[92m+ OpenLibm_jll v0.8.1+0\u001b[39m\n",
+      "\u001b[36m\u001b[1m        Info\u001b[22m\u001b[39m Packages marked with \u001b[33m⌅\u001b[39m have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`\n",
+      "\u001b[32m\u001b[1mPrecompiling\u001b[22m\u001b[39m "
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "project...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mSnoopPrecompile\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStatsAPI\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mJLLWrappers\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mPkgVersion\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mLogExpFunctions\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mSimpleTraits\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mProgressMeter\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mIntelOpenMP_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImath_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mlibpng_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mLERC_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mJpegTurbo_jll\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mZstd_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mFFTW_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mDistances\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mArrayInterfaceCore\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mCPUSummary\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mlibsixel_jll\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mOpenEXR_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mDistances → DistancesSparseArraysExt\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mLibtiff_jll\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mRecipesBase\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mPolyesterWeave\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mLogExpFunctions → LogExpFunctionsChainRulesCoreExt\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mOpenEXR\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageMagick_jll\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStatsBase\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mColorSchemes\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStaticArrays\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mAdapt → AdaptStaticArraysExt\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStaticArrays → StaticArraysStatisticsExt\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mCoordinateTransformations\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mArnoldiMethod\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mArrayInterface\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mArrayInterface → ArrayInterfaceStaticArraysCoreExt\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mRegionTrees\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mOffsetArrays\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mRotations\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStackViews\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mCatIndices\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mPaddedViews\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mMosaicViews\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStaticArrayInterface\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mNearestNeighbors\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStaticArrayInterface → StaticArrayInterfaceOffsetArraysExt\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mCloseOpenIntervals\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mLayoutPointers\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mStaticArrayInterface → StaticArrayInterfaceStaticArraysExt\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mInterpolations\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mTiledIteration\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mClustering\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mGraphs\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mSimpleWeightedGraphs\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mPolynomials\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mJLD2\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mPolynomials → PolynomialsChainRulesCoreExt\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mVectorizationBase\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mMetaGraphs\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mSLEEFPirates\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mMKL_jll\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageCore\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mSixel\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mJpegTurbo\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageBase\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mHistogramThresholding\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageMagick\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageShow\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageAxes\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mPNGFiles\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageTransformations\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageBinarization\u001b[39m\n",
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageMetadata\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mFFTW\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mFFTViews\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mNetpbm\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageContrastAdjustment\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mTiffImages\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageIO\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mLoopVectorization\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageMorphology\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageDistances\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageFiltering\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageSegmentation\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageCorners\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39m\u001b[90mImageQualityIndexes\u001b[39m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39mImages\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m  ✓ \u001b[39mimageToolBox\n",
+      "  87 dependencies successfully precompiled in 84 seconds. 88 already precompiled.\n",
+      "  \u001b[33m2\u001b[39m dependencies had warnings during precompilation:\u001b[33m\n",
+      "┌ \u001b[39mMKL_jll [856f044c-d86e-5d09-b602-aeab76dc8ba7]\u001b[33m\n",
+      "│  \u001b[39m\u001b[32m\u001b[1m Downloading\u001b[22m\u001b[39m artifact: MKL\u001b[33m\n",
+      "└  \u001b[39m\u001b[33m\n",
+      "┌ \u001b[39mimageToolBox [308a64e0-2da8-4ffc-993f-c99ea7c8dc9b]\u001b[33m\n",
+      "│  \u001b[39m\u001b[32m\u001b[1m  Activating\u001b[22m\u001b[39m new project at `~/Desktop/imageToolBox.jl`\u001b[33m\n",
+      "└  \u001b[39m\n"
+     ]
+    }
+   ],
+   "source": [
+    "using Pkg\n",
+    "Pkg.activate(\".\")\n",
+    "Pkg.add(\"Images\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Julia 1.9.2",
+   "language": "julia",
+   "name": "julia-1.9"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "1.9.2"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}