Update app.py

app.py

@@ -20,7 +20,7 @@ import datasets
 from torch.utils.data import Dataset, DataLoader
 
 # For Display
-from tqdm.notebook import tqdm
+#from tqdm.notebook import tqdm
 
 # Other Generic Libraries
 import torch
@@ -96,7 +96,7 @@ def prod_function(transformer_model, prod_dl, prod_data):
 
     prod_preds = []
 
-    for batch in tqdm(acclerated_prod_dl):
+    for batch in acclerated_prod_dl:
         with torch.no_grad():
             emb = accelerated_model(**batch)
         distance = F.pairwise_distance(emb, emb_prod)
@@ -131,7 +131,7 @@ class CreateDatasetProd():
 
     def get_pixels(self, img_paths):
         pixel_values = []
-        for path in tqdm(img_paths):
+        for path in img_paths:
             # Read and process Images
             img = PIL.Image.open(path)
             img = self.transform_prod(img)
@@ -156,8 +156,8 @@ image_paths = []
 image_file = glob(os.path.join(data_path, '*.jpg'))
 #st.write(image_file)
 image_paths.extend(image_file)
-st.write('input path size:', len(image_paths))
-st.write(image_paths)
+#st.write('input path size:', len(image_paths))
+#st.write(image_paths)
 
 # Create DataLoader for Employees image
 dataset_prod_obj = CreateDatasetProd(image_processor_prod)
@@ -168,19 +168,19 @@ prod_dl = DataLoader(prod_ds, batch_size=BATCH_SIZE)
 prod_inputs = next(iter(prod_dl))
 st.write(prod_inputs['pixel_values'].shape) 
 
-## Read image from Camera
-#enable = st.checkbox("Enable camera")
-#picture_path = st.camera_input("Take a picture", disabled=not enable)
-#if picture_path:
-#    # Create DataLoader for Webcam Image
-#    webcam_ds = dataset_prod_obj.create_dataset(picture_path)
-#    webcam_dl = DataLoader(webcam_ds, batch_size=BATCH_SIZE)
-#
-#
-#prediction = prod_function(model_pretrained, prod_dl, webcam_dl)
-#predictions = torch.cat(prediction, 0).to('cpu')
-#match_idx = torch.argmin(predictions)
-#if predictions[match_idx] <= 0.3:
-#  st.write('Welcome: ',image_paths[match_idx].split('/')[-1].split('.')[0])
-#else:
-#  st.write("Match not found")
+# Read image from Camera
+enable = st.checkbox("Enable camera")
+picture_path = st.camera_input("Take a picture", disabled=not enable)
+if picture_path:
+    # Create DataLoader for Webcam Image
+    webcam_ds = dataset_prod_obj.create_dataset(picture_path)
+    webcam_dl = DataLoader(webcam_ds, batch_size=BATCH_SIZE)
+
+
+prediction = prod_function(model_pretrained, prod_dl, webcam_dl)
+predictions = torch.cat(prediction, 0).to('cpu')
+match_idx = torch.argmin(predictions)
+if predictions[match_idx] <= 0.3:
+  st.write('Welcome: ',image_paths[match_idx].split('/')[-1].split('.')[0])
+else:
+  st.write("Match not found")