added logging

app.py

@@ -20,20 +20,27 @@ from tddfa.TDDFA import TDDFA
 import torch.optim as optim
 from DSDG.DUM.models.CDCNs_u import Conv2d_cd, CDCN_u
 
+import io
+import uuid
+import numpy as np
+from PIL import Image
+import boto3
+
 import os
 os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
 os.environ['OMP_NUM_THREADS'] = '4'
 
+app_version = 'ddn1'
 
 device = torch.device("cpu")
 labels = ['Live', 'Spoof']
 pix_threshhold = 0.45
 dsdg_threshold = 0.003
 examples = [
-    ['examples/1_1_21_2_33_scene_fake.jpg', "DeePixBiS"],
-    ['examples/frame150_real.jpg', "DeePixBiS"],
-    ['examples/1_2.avi_125_real.jpg', "DeePixBiS"],
-    ['examples/1_3.avi_25_fake.jpg', "DeePixBiS"]]
+    ['examples/1_1_21_2_33_scene_fake.jpg'],
+    ['examples/frame150_real.jpg'],
+    ['examples/1_2.avi_125_real.jpg'],
+    ['examples/1_3.avi_25_fake.jpg']]
 faceClassifier = cv.CascadeClassifier('./DeePixBiS/Classifiers/haarface.xml')
 tfms = transforms.Compose([
     transforms.ToPILImage(),
@@ -104,7 +111,7 @@ def find_largest_face(faces):
     return largest_face
 
 
-def inference(img, btn_res):
+def inference(img):
     grey = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
     faces = faceClassifier.detectMultiScale(
         grey, scaleFactor=1.1, minNeighbors=4)
@@ -169,26 +176,62 @@ def inference(img, btn_res):
         cv.putText(img_dsdg, label_dsdg, (x, y + h + 30),
                     cv.FONT_HERSHEY_COMPLEX, 1, color_dsdg)
 
-        return img_deepix, confidences_deepix, img_dsdg, confidences_dsdg
+        cls_deepix, cls_dsdg = [1 if cls_ == 'Real' else 0 for cls_ in [cls_deepix, cls_dsdg]]         
+
+        return img_deepix, confidences_deepix, img_dsdg, confidences_dsdg, cls_deepix, cls_dsdg
     else:
-        return img, {}, img, {}
-    
-def open_link():
-    import webbrowser
-    webbrowser.open("https://forms.gle/oEum7W2bQQZ8ctAr7")
+        return img, {}, img, {}, None, None
 
-# Create a button that opens a link when clicked
-button = gr.Button(label="Open link", onclick=open_link)
 
+def upload_to_s3(image_array, app_version, *labels):
+    folder = 'demo'
+    bucket_name = 'livenessng'
 
-if __name__ == '__main__':
-    demo = gr.Interface(
-        fn=inference,
-        inputs=[gr.Image(source='webcam', shape=None, type='numpy'), button],
+    # Initialize S3 client
+    s3 = boto3.client('s3')
+
+    # Encode labels and app version in image file name
+    encoded_labels = '_'.join([str(label) for label in labels])
+    random_string = str(uuid.uuid4()).split('-')[-1]
+    image_name = f"{folder}/{app_version}/{encoded_labels}_{random_string}.jpg"
+
+    # Save image as JPEG
+    image = Image.fromarray(np.uint8(image_array * 255))
+    image_bytes = io.BytesIO()
+    image.save(image_bytes, format='JPEG')
+    image_bytes.seek(0)
+
+    # Upload image to S3
+    res = s3.upload_fileobj(image_bytes, bucket_name, image_name)
+    # Return the S3 URL of the uploaded image
+    status = 'Successfully uploaded'
+    return status
+
+
+# interface = .queue(concurrency_count=2)
+demo = gr.Blocks()
+
+with demo:
+    input_img = gr.Image(source='webcam', shape=None, type='numpy')
+    btn_run = gr.Button(value="Run")
+    with gr.Column():
         outputs=[
             gr.Image(label='DeePixBiS', type='numpy'),
             gr.Label(num_top_classes=2, label='DeePixBiS'),
             gr.Image(label='DSDG', type='numpy'),
-            gr.Label(num_top_classes=2, label='DSDG')],
-        examples=examples).queue(concurrency_count=2)
+            gr.Label(num_top_classes=2, label='DSDG')]
+    labels = [gr.Number(visible=False), gr.Number(visible=False)]
+    btn_run.click(inference, [input_img], outputs+labels)
+
+    app_version_block = gr.Textbox(value=app_version, visible=False)
+    with gr.Column():
+        radio = gr.Radio(
+            ["Real", "Spoof", "None"], label="True label", type='index'
+        )
+        flag = gr.Button(value="Flag")
+        status = gr.Textbox()
+        flag.click(upload_to_s3, [input_img, app_version_block, radio]+labels, [status], show_progress=True)
+
+
+if __name__ == '__main__':
     demo.launch(share=False)

requirements.txt

@@ -9,4 +9,5 @@ scipy
 onnx
 onnxruntime
 cython
+boto3
 --index-url=https://download.pytorch.org/whl/cpu --extra-index-url=https://pypi.org/simple