updat

app.py

@@ -19,8 +19,8 @@ import torchvision
 from huggingface_hub import HfApi, login, snapshot_download
 from PIL import Image
 
-session_token = os.environ.get("SessionToken")
-login(token=session_token)
+# session_token = os.environ.get("SessionToken")
+# login(token=session_token)
 
 csv.field_size_limit(sys.maxsize)
 
@@ -100,22 +100,24 @@ def generate_dataset(username):
 
     NUMBER_OF_IMAGES = len(bad_items)
 
+    print(f"NUMBER_OF_IMAGES: {NUMBER_OF_IMAGES}")
+    print(f"Remaining: {len(remaining)}")
+
     if NUMBER_OF_IMAGES == 0:
         return []
 
-    random_indices = remaining
-    random_images = [imagenet_hard[int(i)]["image"] for i in random_indices]
-    random_gt_ids = [imagenet_hard[int(i)]["label"] for i in random_indices]
-    random_gt_labels = [imagenet_hard[int(x)]["english_label"] for x in random_indices]
+    # random_indices = remaining
+    # random_images = [imagenet_hard[int(i)]["image"] for i in random_indices]
+    # random_gt_ids = [imagenet_hard[int(i)]["label"] for i in random_indices]
+    # random_gt_labels = [imagenet_hard[int(x)]["english_label"] for x in random_indices]
 
     data = []
-    for i, image in enumerate(random_images):
+    for i, image in enumerate(remaining):
         data.append(
             {
-                "id": random_indices[i],
-                "image": image,
-                "correct_label": random_gt_labels[i],
-                "original_id": int(random_indices[i]),
+                "id": remaining[i],
+                # "correct_label": random_gt_labels[i],
+                # "original_id": int(random_indices[i]),
             }
         )
     return data
@@ -153,16 +155,22 @@ def get_training_samples(qid):
 
 def load_sample(data, current_index):
     image_id = data[current_index]["id"]
-    qimage = data[current_index]["image"]
+    qimage = imagenet_hard[int(image_id)]["image"]
+    # labels = data[current_index]["correct_label"]
+    labels = imagenet_hard[int(image_id)]["english_label"]
+    # print(f"Image ID: {image_id}")
+    # print(f"Labels: {labels}")
 
-    labels = data[current_index]["correct_label"]
     return qimage, labels
 
 
 def preprocessing(data, current_index, history, username):
     data = generate_dataset(username)
 
-    if len(data) == 0:
+    remaining_images = len(data)
+    labeled_images = len(bad_items) - remaining_images
+
+    if remaining_images == 0:
         fake_plot = string_to_image("No more images to review")
         empty_image = Image.new("RGB", (224, 224))
         return (
@@ -172,6 +180,7 @@ def preprocessing(data, current_index, history, username):
             history,
             data,
             None,
+            labeled_images,
         )
 
     current_index = 0
@@ -186,7 +195,15 @@ def preprocessing(data, current_index, history, username):
     labels = ", ".join(labels)
     label_plot = string_to_image(labels)
 
-    return qimage, label_plot, current_index, history, data, training_samples_image
+    return (
+        qimage,
+        label_plot,
+        current_index,
+        history,
+        data,
+        training_samples_image,
+        labeled_images,
+    )
 
 
 def update_app(decision, data, current_index, history, username):
@@ -194,7 +211,7 @@ def update_app(decision, data, current_index, history, username):
     if current_index == -1:
         fake_plot = string_to_image("Please Enter your username and load samples")
         empty_image = Image.new("RGB", (224, 224))
-        return empty_image, fake_plot, current_index, history, data, None
+        return empty_image, fake_plot, current_index, history, data, None, 0
 
     if current_index == NUMBER_OF_IMAGES - 1:
         time_stamp = int(time.time())
@@ -226,7 +243,19 @@ def update_app(decision, data, current_index, history, username):
 
         fake_plot = string_to_image("Thank you for your time!")
         empty_image = Image.new("RGB", (224, 224))
-        return empty_image, fake_plot, current_index, history, data, None
+
+        remaining_images = len(data)
+        labeled_images = (len(bad_items) - remaining_images) + current_index
+
+        return (
+            empty_image,
+            fake_plot,
+            current_index,
+            history,
+            data,
+            None,
+            labeled_images + 1,
+        )
 
     if current_index >= 0 and current_index < NUMBER_OF_IMAGES - 1:
         time_stamp = int(time.time())
@@ -270,7 +299,18 @@ def update_app(decision, data, current_index, history, username):
         labels = ", ".join(labels)
         label_plot = string_to_image(labels)
 
-        return qimage, label_plot, current_index, history, data, training_samples_image
+        remaining_images = len(data)
+        labeled_images = (len(bad_items) - remaining_images) + current_index
+
+        return (
+            qimage,
+            label_plot,
+            current_index,
+            history,
+            data,
+            training_samples_image,
+            labeled_images,
+        )
 
 
 newcss = """
@@ -313,7 +353,11 @@ with gr.Blocks(css=newcss, theme=gr.themes.Soft()) as demo:
     )
 
     with gr.Column():
-        username = gr.Textbox(label="Username", value=f"user-{random_str}")
+        with gr.Row():
+            username = gr.Textbox(label="Username", value=f"user-{random_str}")
+            labeled_images = gr.Textbox(label="Labeled Images", value="0")
+            total_images = gr.Textbox(label="Total Images", value=len(bad_items))
+
         prepare_btn = gr.Button(value="Load Samples")
 
     with gr.Column():
@@ -341,6 +385,7 @@ with gr.Blocks(css=newcss, theme=gr.themes.Soft()) as demo:
             history,
             data_gr,
             training_samples,
+            labeled_images,
         ],
     )
     myabe_btn.click(
@@ -353,6 +398,7 @@ with gr.Blocks(css=newcss, theme=gr.themes.Soft()) as demo:
             history,
             data_gr,
             training_samples,
+            labeled_images,
         ],
     )
 
@@ -366,6 +412,7 @@ with gr.Blocks(css=newcss, theme=gr.themes.Soft()) as demo:
             history,
             data_gr,
             training_samples,
+            labeled_images,
         ],
     )
 
@@ -379,7 +426,8 @@ with gr.Blocks(css=newcss, theme=gr.themes.Soft()) as demo:
             history,
             data_gr,
             training_samples,
+            labeled_images,
         ],
     )
 
-demo.launch()
+demo.launch(debug=True)