multiprocess and examples

cedula/app.py

@@ -7,6 +7,7 @@ from transformers import DonutProcessor, VisionEncoderDecoderModel
 import torch
 from PIL import Image
 from pathlib import Path
+import multiprocessing
 
 from models.experimental import attempt_load
 from utils.datasets import LoadImage
@@ -17,6 +18,9 @@ import cv2
 
 key = str(os.environ.get('key'))
 
+desired_num_threads = multiprocessing.cpu_count()
+torch.set_num_threads(desired_num_threads)
+
 def check_image(image):
     try:
         images = convert_from_path(Path(image.name), fmt="jpeg", size=(960,1280))
@@ -94,8 +98,8 @@ def crop(files = '', #files
 def get_attributes(input_img):
     #access_token = str(os.environ.get('key'))
     access_token = key
-    processor = DonutProcessor.from_pretrained("ClipAI/license-demo", use_auth_token=access_token)
-    model = VisionEncoderDecoderModel.from_pretrained("ClipAI/license-demo", use_auth_token=access_token)
+    processor = DonutProcessor.from_pretrained("ClipAI/cedula-demo", use_auth_token=access_token)
+    model = VisionEncoderDecoderModel.from_pretrained("ClipAI/cedula-demo", use_auth_token=access_token)
 
     device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -143,6 +147,16 @@ def get_attributes(input_img):
 #demo.launch()
 
 def create_model():
+    demo = gr.Interface(get_attributes,
+                        "image",
+                        "json",
+                        examples=[["examples/cedula1.jpg"]]
+                        )
+    return demo
+
+
+
+def create_model2():
     with gr.Blocks() as demo:
         with gr.Row():
             with gr.Column():

license/app.py

@@ -7,6 +7,7 @@ from transformers import DonutProcessor, VisionEncoderDecoderModel
 import torch
 from PIL import Image
 from pathlib import Path
+import multiprocessing
 
 from models.experimental import attempt_load
 from utils.datasets import LoadImage
@@ -17,6 +18,9 @@ import cv2
 
 key = str(os.environ.get('key'))
 
+desired_num_threads = multiprocessing.cpu_count()
+torch.set_num_threads(desired_num_threads)
+
 def check_image(image):
     try:
         images = convert_from_path(Path(image.name), fmt="jpeg", size=(960,1280))
@@ -141,10 +145,14 @@ def get_attributes(input_img):
 #demo.launch()
 
 def create_model():
-    demo = gr.Interface(get_attributes, "image", "json")
+    demo = gr.Interface(get_attributes,
+                        "image",
+                        "json",
+                        examples=[["examples/license1.jpg"]]
+                        )
     return demo
 
-
+["examples/licencia.jpg"]
 if __name__ == '__main__':
     demo = create_model()
     demo.launch()