equalisation fonctionnelle

Author: apachefranklin

imgprocess/img_api.py

@@ -8,6 +8,12 @@
 from .utils.utility import *
 from PIL import Image
 import numpy as np
+from matplotlib import pyplot as plt
+
+img_path="imgprocess/static/imageprocess/images/"
+hist_path=img_path+"hist/"
+hist_path_result=img_path+"histresult/"
+result_path=img_path+"result/"
 
 def _constrate(request):
     image_file=request.FILES["imguploaded"]
@@ -35,4 +41,38 @@ def _constrate(request):
     return JsonResponse({"original_name":str(image_file),"extention":file_extension,"saved_name":saved_name})
 
 def _egalisation_histogramme(request):
-    return JsonResponse({"status":True})
+    """At the end we need to send the preview histogramme, the new histgramme
+    and the final image"""
+    image_info=save_image(request.FILES["imguploaded"],None)
+    
+    #we get the name of the preview_histogramme
+    preview_his_name=get_random_string(20)+image_info["extension"];
+    plt.hist(image_info["list"]);
+
+    plt.savefig(hist_path+preview_his_name)
+    plt.close()
+
+   
+    image_info["preview_hist"]=preview_his_name
+
+    #we call function of equalisation on the matrix of image
+    egalisation_his_matrix=ImgLib().histogram_normalisation(image_info["matrix"])
+    #we get now the new image 
+
+    print(egalisation_his_matrix)
+
+    new_image=Image.fromarray(egalisation_his_matrix.astype(np.uint8))
+    new_image_name=get_random_string(18)+image_info["extension"]
+    new_image.save(result_path+new_image_name)
+
+    #now we reshape our egalisation_his_matirx at the list and we create the plot
+    new_image_as_list=egalisation_his_matrix.ravel()
+    new_his_name=get_random_string(24)+image_info["extension"]
+    plt.plot(new_image_as_list)
+    plt.savefig(hist_path_result+new_his_name);
+    plt.close()
+    image_info["new_hist"]=new_his_name
+    image_info["saved_name"]=new_image_name
+    image_info["matrix"]=None
+    
+    return JsonResponse(image_info)

imgprocess/static/shared/js/img_process.js

@@ -21,13 +21,38 @@ $(function(e){
             dataType: "json",
             method:"POST",
             success:function(result){
-                console.log("bonjour")
+                console.log(result);
                 $("#result-box").html("<img src='/static/imageprocess/images/result/"+result["saved_name"]+"' width='100%' height='100%' />");
             },
             error:function(result){
-                console.log("error")
+                console.log("error");
             }
         });
         return false;
     });
+
+
+    $("#form_equalize").submit(function(){
+        
+        form_data=new FormData(this)
+        $.ajax({
+            url:$(this).attr("action"),
+            data:form_data,
+            contentType: false,
+            cache: false,
+            processData: false,
+            dataType: "json",
+            method:"POST",
+            success:function(result){
+                console.log(result);
+                $("#result-box").html("<img src='/static/imageprocess/images/result/"+result["saved_name"]+"' width='100%' height='100%' />");
+                $("#hist-preview").html("<img src='/static/imageprocess/images/hist/"+result["preview_hist"]+"' width='100%' height='100%' />");
+                $("#hist-result-box").html("<img src='/static/imageprocess/images/histresult/"+result["new_hist"]+"' width='100%' height='100%' />");
+            },
+            error:function(result){
+                console.log("error");
+            }
+        });
+        return false;
+    })
 });

imgprocess/templates/imgprocess/egalisation_histogramme.html

@@ -9,7 +9,7 @@
         <h1>Welcome to histogramme egalisation</h1>
         <hr />
         <br />
-        <form class="" id="form_upload_image" enctype="multipart/form-data" ajax method="post" action="{% url 'imageprocess:pluminecance' %}">
+        <form class="" id="form_equalize" enctype="multipart/form-data" ajax method="post" action="{% url 'imageprocess:pegalisation' %}">
         {% csrf_token %}
         <div class="row">
         </div>
@@ -24,15 +24,33 @@ <h4>Preview</h4>
             </div>
             <div class="col-6">
                 <h4>histogramme Preview</h4>
+                <div class="card border-0 shadow-lg" id="hist-preview">
+                    
+                </div>
+                <br />
+                  <button type="submit" class="btn btn-info rounded btn-lg second-color shadow-lg text-white">EQUALIZE</button>
+
+            </div>
+            <!--result with histogramme -->
+            <div class="col-6">
+            <br />
+                <h4>Obtained Image</h4>
                 <div class="card border-0 shadow-lg" id="result-box">
 
+                </div>
+            </div>
+            <div class="col-6">
+            <br />
+                <h4>Obtained  Histogramm</h4>
+                <div class="card border-0 shadow-lg" id="hist-result-box">
+                    
                 </div>
             </div>
         </div>
         <br />
         <br />
         <label>After click look result down</label><br />
-        <button type="submit" class="btn btn-info rounded btn-lg second-color shadow-lg text-white">EQUALIZE</button>
+      
         </form>
     </div>
     {% endblock %}

imgprocess/utils/__init__.py

@@ -81,10 +81,15 @@ def histogram_normalisation(self,img_matrix):
         #normalisation of probality density
         c_normalize=[[],[]]
         new_image=np.zeros(img_matrix.shape,dtype=int)
-        for i in list(range(1,256)):
-            c_normalize[i-1]=0
-            for j in list(range(i)):
-                pass
+        #Calcul des densite de probabablite
+        c_normalize=np.cumsum(h_normalize)
+
+        for i in range(img_matrix.shape[0]):
+            for j in range(img_matrix.shape[1]):
+                img_matrix[i][j]=c_normalize[img_matrix[i][j]]*255
+        
+        return img_matrix
+
 
 
 

imgprocess/utils/img_lib.py

@@ -1,5 +1,10 @@
 import string
 import random
+from PIL import Image
+from .img_lib import ImgLib
+import os
+import numpy as np
+
 
 def get_random_string(length):
     letters = string.ascii_lowercase
@@ -14,4 +19,30 @@ def handle_uploaded_file(f,namepath_to_upload):
 
 def move_upload_image(img_data,file_name):
      with open('imageprocess/static/imageprocess/images/'+file_name, 'wb+') as destination:
-         destination.write(img_data)
+         destination.write(img_data)
+
+
+def save_image(image_file,image_path):
+    
+    """ That function return the saved name, 
+        the path and the matrix of image
+    """
+   
+    file_name,file_extension=os.path.splitext(str(image_file))
+    saved_name=get_random_string(15)+file_extension
+    handle_uploaded_file(image_file,"imgprocess/static/imageprocess/images/"+saved_name)
+    
+    imgglib=ImgLib()
+
+    img_final=Image.open("imgprocess/static/imageprocess/images/"+saved_name)
+
+    img_list_data=list(img_final.getdata())
+
+    img_matrix=np.reshape(img_list_data,img_final.size)
+
+    return {"matrix":img_matrix,
+            "path":"imgprocess/static/imageprocess/images/"+saved_name,
+            "name":saved_name,
+            "list":img_list_data,
+            "extension":file_extension}
+