img is cropped and transformed to torch

.idea/workspace.xml

@@ -19,16 +19,10 @@
     <select />
   </component>
   <component name="ChangeListManager">
-    <list default="true" id="828778c9-9d97-422f-a727-18ddbd059b85" name="Default Changelist" comment="add coder.py">
+    <list default="true" id="828778c9-9d97-422f-a727-18ddbd059b85" name="Default Changelist" comment="detecting digits">
-      <change afterPath="$PROJECT_DIR$/coder/12345.png" afterDir="false" />
-      <change afterPath="$PROJECT_DIR$/coder/ll.png" afterDir="false" />
-      <change afterPath="$PROJECT_DIR$/coder/testno.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/coder/coder.py" beforeDir="false" afterPath="$PROJECT_DIR$/coder/coder.py" afterDir="false" />
-      <change beforePath="$PROJECT_DIR$/coder/digit_reco_model.pt" beforeDir="false" afterPath="$PROJECT_DIR$/coder/digit_reco_model.pt" afterDir="false" />
-      <change beforePath="$PROJECT_DIR$/coder/digit_reco_model2.pt" beforeDir="false" afterPath="$PROJECT_DIR$/coder/digit_reco_model2.pt" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/coder/digits_recognizer.py" beforeDir="false" afterPath="$PROJECT_DIR$/coder/digits_recognizer.py" afterDir="false" />
-      <change beforePath="$PROJECT_DIR$/coder/image.py" beforeDir="false" afterPath="$PROJECT_DIR$/coder/image.py" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/coder/rocognizer.py" beforeDir="false" afterPath="$PROJECT_DIR$/coder/rocognizer.py" afterDir="false" />
     </list>
     <option name="SHOW_DIALOG" value="false" />
@@ -88,7 +82,7 @@
       <recent name="C:\Users\Pawel Lukaszewicz\PycharmProjects\AL-2020\coder\dataset" />
     </key>
   </component>
-  <component name="RunManager" selected="Python.rocognizer">
+  <component name="RunManager" selected="Python.digits_recognizer">
     <configuration default="true" type="PythonConfigurationType" factoryName="Python">
       <module name="wozek" />
       <option name="INTERPRETER_OPTIONS" value="" />
@@ -137,9 +131,6 @@
       <module name="wozek" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
-      <envs>
-        <env name="PYTHONUNBUFFERED" value="1" />
-      </envs>
       <option name="SDK_HOME" value="" />
       <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/coder" />
       <option name="IS_MODULE_SDK" value="true" />
@@ -227,9 +218,9 @@
     </list>
     <recent_temporary>
       <list>
+        <item itemvalue="Python.digits_recognizer" />
         <item itemvalue="Python.rocognizer" />
         <item itemvalue="Python.coder" />
-        <item itemvalue="Python.digits_recognizer" />
         <item itemvalue="Python.z8" />
         <item itemvalue="Python.image" />
       </list>
@@ -272,7 +263,8 @@
       <workItem from="1590518246722" duration="12616000" />
       <workItem from="1590559069326" duration="13892000" />
       <workItem from="1590575699320" duration="792000" />
-      <workItem from="1590766924835" duration="4315000" />
+      <workItem from="1590766924835" duration="10060000" />
+      <workItem from="1590929874289" duration="7728000" />
     </task>
     <task id="LOCAL-00001" summary="create Shelf">
       <created>1589815443652</created>
@@ -365,7 +357,14 @@
       <option name="project" value="LOCAL" />
       <updated>1590538529471</updated>
     </task>
-    <option name="localTasksCounter" value="14" />
+    <task id="LOCAL-00014" summary="detecting digits">
+      <created>1590846768877</created>
+      <option name="number" value="00014" />
+      <option name="presentableId" value="LOCAL-00014" />
+      <option name="project" value="LOCAL" />
+      <updated>1590846768877</updated>
+    </task>
+    <option name="localTasksCounter" value="15" />
     <servers />
   </component>
   <component name="TypeScriptGeneratedFilesManager">
@@ -398,7 +397,8 @@
     <MESSAGE value="new dataset" />
     <MESSAGE value="going to pytorch on conda eve" />
     <MESSAGE value="add coder.py" />
-    <option name="LAST_COMMIT_MESSAGE" value="add coder.py" />
+    <MESSAGE value="detecting digits" />
+    <option name="LAST_COMMIT_MESSAGE" value="detecting digits" />
   </component>
   <component name="WindowStateProjectService">
     <state x="115" y="162" key="#com.intellij.refactoring.safeDelete.UnsafeUsagesDialog" timestamp="1589923610328">
@@ -425,14 +425,14 @@
       <screen x="0" y="0" width="1536" height="824" />
     </state>
     <state x="277" y="57" key="SettingsEditor/0.0.1536.824@0.0.1536.824" timestamp="1590443566792" />
-    <state x="361" y="145" key="Vcs.Push.Dialog.v2" timestamp="1590538563335">
+    <state x="361" y="145" key="Vcs.Push.Dialog.v2" timestamp="1590846777672">
       <screen x="0" y="0" width="1536" height="824" />
     </state>
-    <state x="361" y="145" key="Vcs.Push.Dialog.v2/0.0.1536.824@0.0.1536.824" timestamp="1590538563335" />
+    <state x="361" y="145" key="Vcs.Push.Dialog.v2/0.0.1536.824@0.0.1536.824" timestamp="1590846777672" />
-    <state x="54" y="145" width="672" height="678" key="search.everywhere.popup" timestamp="1589918982407">
+    <state x="54" y="145" width="672" height="678" key="search.everywhere.popup" timestamp="1590930912296">
       <screen x="0" y="0" width="1536" height="824" />
     </state>
-    <state x="54" y="145" width="672" height="678" key="search.everywhere.popup/0.0.1536.824@0.0.1536.824" timestamp="1589918982407" />
+    <state x="54" y="145" width="672" height="678" key="search.everywhere.popup/0.0.1536.824@0.0.1536.824" timestamp="1590930912296" />
   </component>
   <component name="com.intellij.coverage.CoverageDataManagerImpl">
     <SUITE FILE_PATH="coverage/AL_2020$feature_hashing.coverage" NAME="feature_hashing Coverage Results" MODIFIED="1589823737949" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/Assiging" />

coder/coder.py

@@ -52,6 +52,7 @@ plt.show()
 
 with torch.no_grad():
     logps = model(img)
+print(logps)
 
 ps = torch.exp(logps)
 probab = list(ps.numpy()[0])

coder/digits_recognizer.py

@@ -17,6 +17,7 @@ train_set = datasets.MNIST('PATH_TO_STORE_TRAINSET', download=True, train=True,
 val_set = datasets.MNIST('PATH_TO_STORE_TESTSET', download=True, train=False, transform=transform)
 train_loader = torch.utils.data.DataLoader(train_set, batch_size=64, shuffle=True)
 val_loader = torch.utils.data.DataLoader(val_set, batch_size=64, shuffle=True)
+print(train_set[0])
 
 # building nn model
 input_size = 784 # = 28*28

coder/rocognizer.py

@@ -4,10 +4,19 @@ import imutils
 import cv2
 import matplotlib.pyplot as plt
 import torch
+from matplotlib import cm
+from torch import nn
 from PIL import Image
+from skimage.feature import hog
+from torchvision.transforms import transforms
 
+code = []
 path = "test1.jpg"
 
+transform = transforms.Compose([transforms.ToTensor(),
+                                transforms.Normalize((0.5,), (0.5,)),
+                                ])
+
 img = cv2.imread(path)
 
 img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
@@ -19,18 +28,44 @@ ctrs, hier = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_
 
 rects = [cv2.boundingRect(ctr) for ctr in ctrs]
 
+# load nn model
+input_size = 784 # = 28*28
+hidden_sizes = [128, 128, 64]
+output_size = 10
+model = nn.Sequential(nn.Linear(input_size, hidden_sizes[0]),
+                      nn.ReLU(),
+                      nn.Linear(hidden_sizes[0], hidden_sizes[1]),
+                      nn.ReLU(),
+                      nn.Linear(hidden_sizes[1], hidden_sizes[2]),
+                      nn.ReLU(),
+                      nn.Linear(hidden_sizes[2], output_size),
+                      nn.LogSoftmax(dim=-1))
+model.load_state_dict(torch.load('digit_reco_model2.pt'))
+model.eval()
+
 for rect in rects:
-    # Draw the rectangles
+    # Crop image
-    cv2.rectangle(img, (rect[0], rect[1]), (rect[0] + rect[2], rect[1] + rect[3]), (0, 255, 0), 3)
+    crop_img = img[rect[1]:rect[1] + rect[3], rect[0]:rect[0] + rect[2]]
-    # Make the rectangular region around the digit
+    plt.imshow(crop_img)
-    leng = int(rect[3] * 1.6)
+    plt.show()
-    pt1 = int(rect[1] + rect[3] // 2 - leng // 2)
+
-    pt2 = int(rect[0] + rect[2] // 2 - leng // 2)
-    roi = im_th[pt1:pt1+leng, pt2:pt2+leng]
     # Resize the image
-    roi = cv2.resize(roi, (28, 28), interpolation=cv2.INTER_AREA)
+    roi = cv2.resize(crop_img, (28, 28), interpolation=cv2.INTER_AREA)
-    roi = cv2.dilate(roi, (3, 3))
+    plt.imshow(roi)
-    # Calculate the HOG features
+    plt.show()
+    im = Image.fromarray(roi)
+
+    im = transform(im)
+    print(im)
+    plt.imshow(im)
+    plt.show()
+
+    with torch.no_grad():
+        logps = model(im)
+    ps = torch.exp(logps)
+    print(ps[0])
+    probab = list(ps.numpy()[0])
+    print("Predicted Digit =", probab.index(max(probab)))
 
 cv2.imshow("Resulting Image with Rectangular ROIs", img)
 cv2.waitKey()