Update app.py

app.py

@@ -56,19 +56,12 @@ scal = st.checkbox("Scaling")
 shearing=st.checkbox("Shearing")
 crop=st.checkbox("Crop")
 
-
-    
+   
 btn=st.button("Submit")
-# count=len(transformation)
-# for i in range(image_count):
-#     for j in transformation:
-#         if i=="Translation":
-#             tx=250
-#             ty=250
-#             tm=np.array([[1,0,tx],[0,1,ty]],dtype=np.float32)
+
 def transalation(img):
-    tx=np.random.randint(2,60)
-    ty=np.random.randint(2,55)
+    tx=3 #np.random.randint(2,60)
+    ty=5 #np.random.randint(2,55)
     tm=np.array([[1,0,tx],[0,1,ty]],dtype=np.float32)
     trans_img=cv2.warpAffine(img,tm,dsize=(300,300))
     img=cv2.imdecode(trans_img,cv2.IMREAD_COLOR)
@@ -80,12 +73,12 @@ if uploaded_file is not None:
     # Converting the image into array
     img_array=np.asarray(bytearray(uploaded_file.read()),dtype=np.uint8)
     # Decode or converting the array back to image
-    img=cv2.imdecode(img_array,cv2.IMREAD_COLOR)
-     # Convert BGR to RGB as streamlit expects RGB colorspace
-    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    # img=cv2.imdecode(img_array,cv2.IMREAD_COLOR)
+    #  # Convert BGR to RGB as streamlit expects RGB colorspace
+    # img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
     transformation = []
     if trans:
-        transalation(img_rgb)
+        transalation(img_array)
         transformation.append("Translation")
     if rot:
         transformation.append("Rotation")