modifification des types de matrices en uint8

Author: apachefranklin

imgprocess/img_api.py

@@ -136,7 +136,7 @@ def _convolution(request):
         conv_matrix[i,]=elts
 
     image_info=save_image(request.FILES["imguploaded"],img_path)
-    new_img_matrix=ImgLib().convolution(image_info["matrix"],conv_matrix)
+    new_img_matrix=ImgLib().convolution2(image_info["matrix"],conv_matrix)
 
     new_img_matrix=new_img_matrix.astype(np.uint8)
     new_img=Image.fromarray(new_img_matrix)
@@ -180,3 +180,28 @@ def _interpolation(request):
     image_info["list"]=None
     image_info["pgm_name"]=new_image_name+".pgm"
     return JsonResponse(image_info)
+
+def _median_filter(request):
+    voisinage=int(request.POST.get("voisinage",0))
+    img_info=save_image(request.FILES["imguploaded"],None)
+    median_matrix=ImgLib.median_filter(img_info["matrix"],voisinage)
+
+    new_median_matrix=median_matrix.astype(np.uint8)
+    new_img=Image.fromarray(new_median_matrix)
+    #on definit un nouveau nom pour notre image
+    extension=img_info["extension"]
+    if(extension.lower()==".pgm"):
+        extension=".png"
+    
+    new_image_name=get_random_string(24)+extension
+
+    new_img.save(result_path+new_image_name)
+
+    #sauvegarde au format pgm de l'image
+    ImgLib.save_matrix_as_pgm(new_median_matrix,new_image_name)
+
+    img_info["matrix"]=None
+    img_info["saved_name"]=new_image_name
+    img_info["list"]=None
+    img_info["pgm_name"]=new_image_name+".pgm"
+    return JsonResponse(img_info)

imgprocess/static/shared/js/img_process.js

@@ -10,6 +10,14 @@ function showPreview(objFileInput, html_element) {
 
 
 $(function (e) {
+    //on va forcer le telechargement des fichiers pgm
+    $("#download-pgm-result").click(function(){
+        var dname=$(this).attr("data-download")
+        $.get($(this).attr("data-url"),{download_name:dname},function(e){
+            console.log("bojnour")
+        });
+    });
+
     $("#image-viewver").hide();
     $("#image-viewver").click(function () {
         $(this).fadeOut(1000)
@@ -32,6 +40,7 @@ $(function (e) {
             success: function (result) {
                 console.log(result);
                 $("#result-box").html("<img src='/static/imageprocess/images/result/" + result["saved_name"] + "' width='100%' height='100%' />");
+                $("#download-pgm-result").attr("data-download",result["pgm_name"])
             },
             error: function (result) {
                 console.log("error");

imgprocess/templates/imgprocess/constraste.html

@@ -37,6 +37,7 @@ <h4>Result</h4>
                 <div class="card border-0 shadow-lg" id="result-box">
 
                 </div>
+                <button type="button" data-url="{% url 'imageprocess:download' %}" data-download="" id="download-pgm-result" class="btn btn-warning btn-lg text-white">Download PGM RESULT</button>
             </div>
         </div>
         <br />

imgprocess/templates/imgprocess/index.html

@@ -28,7 +28,7 @@ <h3>EGALISATION HISTOGRAMME</h3>
         </div>
 
         <div class="col-lg-3 col-12">
-            <a class="nav-link" href="{% url 'imageprocess:egalisation' %}">
+            <a class="nav-link" href="{% url 'imageprocess:median' %}">
                 <div class="card shadow-lg border-0">
 
                     <h3>FILTRE MEDIAN</h3>

imgprocess/templates/imgprocess/median_filter.html

@@ -0,0 +1,45 @@
+{% extends 'base.html' %}
+
+
+{% block content %}
+    <br />
+    <div class="container">
+        <h1>Welcome to median filter</h1>
+        <hr />
+        <br />
+        <form class="" id="form_upload_image" enctype="multipart/form-data" method="post" action="{% url 'imageprocess:pmedian' %}">
+        {% csrf_token %}
+        <div class="row">
+        <div class="col-12">
+            <!-- <textarea class="form-control form-control-lg"> -->
+            </textarea>
+        </div>
+            <div class="col">
+                <label>Neighborhood</label>
+                <input type="number" name="voisinage" placeholder="
+                neighborhood of 3 means 3x3 so 9" value="0" max="254" min="0" required="true" class="form-control" />
+            </div>
+        </div>
+        <div class="row img-list-work">
+            <div class="col-6">
+                <h4>Preview</h4>
+                <div class="card border-0 shadow-lg" id="img_preview">
+                    
+                </div>
+                <label>upload image</label>
+                <input type="file" name="imguploaded"  class="form-control form-control-file" onChange="showPreview(this,'#img_preview')" />
+            </div>
+            <div class="col-6">
+                <h4>Result</h4>
+                <div class="card border-0 shadow-lg" id="result-box">
+                    
+                </div>
+                <button type="button" data-url="{% url 'imageprocess:download' %}" data-download="" id="download-pgm-result" class="btn btn-warning btn-lg text-white">Download PGM RESULT</button>
+            </div>
+        </div>
+        <br />
+        <br />
+        <button type="submit" class="btn btn-info rounded btn-lg second-color shadow-lg text-white">MEDIAN FILTER</button>
+        </form>
+    </div>
+{% endblock content %}

imgprocess/urls.py

@@ -17,5 +17,8 @@
     path("pconvolution",img_api._convolution,name="pconvolution"),
 
     path("interpolation",views.interpolation,name="interpolation"),
-    path("pinterpolation",img_api._interpolation,name="pinterpolation")
+    path("pinterpolation",img_api._interpolation,name="pinterpolation"),
+    path("download",views.download_file,name="download"),
+    path("median_filter",views.median_filter,name="median"),
+    path("pmedian_filter",img_api._median_filter,name="pmedian")
 ]

imgprocess/utils/img_lib.py

@@ -91,7 +91,7 @@ def linea_transformation(cls,img_matrix,saturation_min=0,saturation_max=0):
         differecence=max_pixel-min_pixel
         lumine=np.mean(img_matrix)
         dimesnion=img_matrix.shape
-        new_image=np.zeros(dimesnion,dtype=int)
+        new_image=np.zeros(dimesnion,dtype="uint8")
         for i in range(dimesnion[0]):
             for j in range(dimesnion[1]):
                 new_image[i][j]=int((255/differecence)*(img_matrix[i][j]-min_pixel))
@@ -154,7 +154,7 @@ def add_two_image(cls,img_matrix1,img_matrix2,mult_fact_1=1,mult_fact_2=1):
         """That function take two image matrix in parameter, supooe to be the same and 
         make the summ"""
         dimension=img_matrix1.shape
-        new_matrix=np.zeros(dimension)
+        new_matrix=np.zeros(dimension,dtype="uint8")
         for i in range(dimension[0]):
             for j in range(dimension[1]):
                 pixel=img_matrix1[i][j]*mult_fact_1+img_matrix2[i][j]*mult_fact_2
@@ -168,7 +168,7 @@ def subtract_two_image(cls,img_matrix1,img_matrix2,mult_fact_1=1,mult_fact_2=1):
         """That function take two image matrix in parameter, supooe to be the same and 
         make the subtraction"""
         dimension=img_matrix1.shape
-        new_matrix=np.zeros(dimension)
+        new_matrix=np.zeros(dimension,dtype="uint8")
         for i in range(dimension[0]):
             for j in range(dimension[1]):
                 pixel=img_matrix1[i][j]*mult_fact_1-img_matrix2[i][j]*mult_fact_2
@@ -182,7 +182,7 @@ def subtract_two_image(cls,img_matrix1,img_matrix2,mult_fact_1=1,mult_fact_2=1):
     def or_operation(cls,img_matrix1,img_matrix2):
         """Take to image matrix and make the or operation"""
         dimension=img_matrix1.shape
-        new_matrix=np.zeros(dimension)
+        new_matrix=np.zeros(dimension,dtype="uint8")
         for i in range(dimension[0]):
             for j in range(dimension[1]):
                 new_matrix[i][j]=int(img_matrix1[i][j])|int(img_matrix2[i][j])
@@ -192,7 +192,7 @@ def or_operation(cls,img_matrix1,img_matrix2):
     def and_operation(cls,img_matrix1,img_matrix2):
         """Take to image matrix and make the and operation"""
         dimension=img_matrix1.shape
-        new_matrix=np.zeros(dimension)
+        new_matrix=np.zeros(dimension,dtype="uint8")
         for i in range(dimension[0]):
             for j in range(dimension[1]):
                 new_matrix[i][j]=int(img_matrix1[i][j]) & int(img_matrix2[i][j])
@@ -230,13 +230,13 @@ def convolution2(cls,img_matrix,kernel):
         center=int((kernel.shape[1]-1)/2)
         dimension=img_matrix.shape
         kernel_shape=kernel.shape
-        new_img_matrix=np.zeros(img_matrix.shape,dtype=int)
+        new_img_matrix=np.zeros(img_matrix.shape,dtype="uint8")
         for i in range(center,dimension[0]-center):
             for j in range(center,dimension[1]-center):
                 pixel_somme=0
                 for u in range(kernel_shape[0]):
                     for v in range(kernel_shape[1]):
-                        pixel_somme+=img_matrix[i-u][j-v]*kernel[u][v]
+                        pixel_somme+=img_matrix[i-u-1][j-v-1]*kernel[u][v]
                 pixel_somme=int(pixel_somme)
                 if(pixel_somme<0):
                     pixel_somme=0
@@ -283,7 +283,17 @@ def save_matrix_as_pgm(cls,img_matrix,name):
         with open("imgprocess/static/imageprocess/images/result/"+name+".pgm","w+") as f:
             f.write(data_to_write)
 
-
+    @classmethod
+    def median_filter(cls,img_matrix,voisinage):
+        center=int(voisinage/2)
+        dimension=img_matrix.shape
+        new_img_matrix=np.zeros(img_matrix.shape,dtype=int)
+        for i in range(center,dimension[0]-center):
+            for j in range(center,dimension[1]-center):
+                voisinnage=img_matrix[i-center:i+center+1,j-center:j+center+1]
+                #print(voisinnage.shape)
+                new_img_matrix[i][j]=np.median(np.reshape(voisinnage,voisinage*voisinage))
+        return new_img_matrix
 
 
 

imgprocess/utils/utility.py

@@ -6,6 +6,10 @@
 import numpy as np
 import random,math
 
+img_path="imgprocess/static/imageprocess/images/"
+hist_path=img_path+"hist/"
+hist_path_result=img_path+"histresult/"
+result_path=img_path+"result/"
 
 def get_random_string(length):
     letters = string.ascii_lowercase

imgprocess/views.py

@@ -10,8 +10,11 @@
 import numpy as np
 # Create your views here.
 
-def download_file(request,path):
-    pass
+def download_file(request):
+    file_name=request.GET["download_name"]
+    response =FileResponse(open(result_path+file_name,"r"))
+    
+    return response
 
 def index(request):
     return render(request,"imgprocess/index.html")
@@ -48,3 +51,6 @@ def author(request):
 
 def interpolation(request):
     return render(request,"imgprocess/interpolation.html")
+
+def median_filter(request):
+    return render(request,"imgprocess/median_filter.html")