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deploy.py

@@ -10,13 +10,25 @@ from paddleocr import PaddleOCR
 from app.layoutLM_api.api import custom_ocr
 import cv2
 
-def ocr(input_img):
-    print(type(input_img))
-    ocr = PaddleOCR(use_angle_cls=True, lang='en') # need to run only once to download and load model into memory
+def ocr(image_input, webcam_input):
 
     file_path = 'app/images/idcards/input.jpg'
-    cv2.imwrite(file_path, input_img)
 
+    print("image_input : ", type(image_input))
+    print("Webcam Image : ", type(webcam_input))
+
+    if image_input is not None and image_input.any():
+        print("In input image")
+        cv2.imwrite(file_path, image_input)
+    else:
+        print("In webcam")
+        cv2.imwrite(file_path, webcam_input)
+    
+    # print(type(input_img))
+    ocr = PaddleOCR(use_angle_cls=True, lang='en') # need to run only once to download and load model into memory
+
+    
+    
     # with open(file_path, "wb+") as file_object:
     #     file_object.write(input_img.file.read())
     
@@ -59,5 +71,12 @@ def ocr(input_img):
     response = {"Status" : 200, "OCR" : dictionary}  
     return response
 
-demo = gr.Interface(ocr, gr.Image(), "json")
-demo.launch(share=True)
+# webcam_checkbox = gr.inputs.Checkbox(label="Use webcam", optional=True)
+
+# Define the input objects
+image_input = gr.inputs.Image(label="Upload Image")
+webcam_input = gr.inputs.Image(label="Webcam", source="webcam")
+
+# Create the Gradio interface
+interface = gr.Interface(fn=ocr, inputs=[image_input, webcam_input], outputs="json")
+interface.launch(share=True)

flagged/log.csv

@@ -0,0 +1,2 @@
+Input Image,component 1,output,flag,username,timestamp
+/home/shahzain/Documents/Voltox Ai Servers/OCR/flagged/Input Image/tmp304mlnni.png,/home/shahzain/Documents/Voltox Ai Servers/OCR/flagged/component 1/tmpyy_giqip.jpg,,,,2023-06-06 11:50:58.232590