Update app.py

app.py

@@ -7,38 +7,55 @@ import numpy as np
 import tensorflow.compat.v1 as tf
 import os
 import streamlit as st
+from PIL import Image
+import streamlit as st
 
+def load_image(image_file):
+	img = Image.open(image_file)
+	return img
+	
+	
+st.subheader("Image")
+image_file = st.file_uploader("Upload Images", type=["png","jpg","jpeg"])
 
-model = torch.hub.load('ultralytics/yolov5', 'custom', path='yoloocr_best.pt')
-model.cpu()
-model.conf = 0.5
-license = DetectLicensePlate()
-counter  = dict()
-frame = cv2.imread("")
-try:
-    plate_img = alpr(frame,license)
-    #plate_img = cv2.resize(plate_img,(200,50))
-    results = model(plate_img*255)
-    #print(results.xyxy[0])
-    name = results.pandas().xyxy[0].sort_values('xmin').iloc[:, -1]
-    name = "".join([i for i in name])
-    if name not in counter and name != '':
-        counter[name] = 1
-    if name in counter and name !='':
-        counter[name] +=1
-    plate_name = list((sorted(counter.items(),key = lambda item:item[1])))[-1][0]
-    print(plate_name)
-    coord = results.pandas().xyxy[0].sort_values('xmin').iloc[:,:]
-    if len(coord) == 0:
-        counter.clear()
-
-    cv2.imshow("Plate", plate_img)
-
+#if image_file is not None:
+    # To See details
+    #file_details = {"filename":image_file.name, "filetype":image_file.type,"filesize":image_file.size}
+    #st.write(file_details)
 
+    # To View Uploaded Image
+    #st.image(load_image(image_file),width=250)
+    
+submit = st.button('Generate')
 
-except Exception as e:
+if submit:
+    model = torch.hub.load('ultralytics/yolov5', 'custom', path='yoloocr_best.pt')
+    model.cpu()
+    model.conf = 0.5
+    license = DetectLicensePlate()
+    counter  = dict()
+    frame = cv2.imread(np.array(image_file))
+    try:
+        plate_img = alpr(frame,license)
+        #plate_img = cv2.resize(plate_img,(200,50))
+        results = model(plate_img*255)
+        #print(results.xyxy[0])
+        name = results.pandas().xyxy[0].sort_values('xmin').iloc[:, -1]
+        name = "".join([i for i in name])
+        if name not in counter and name != '':
+            counter[name] = 1
+        if name in counter and name !='':
+            counter[name] +=1
+        plate_name = list((sorted(counter.items(),key = lambda item:item[1])))[-1][0]
+        print(plate_name)
+    
+        #cv2.imshow("Plate", plate_img)
+        st.write(plate_name)
     
-    counter.clear()
-    print("Plaka bulunamadı")
-   
+    
+    except Exception as e:
+        
+        counter.clear()
+        print("Plaka bulunamadı")
+