fixed link in pdf

src/data_gradients/assets/html/doc_template.html

@@ -325,7 +325,7 @@
     {% endfor %}
     <div class="alert-box notice">
         <span><img  src="{{assets.image.info}}" width="40pt" height="25pt">Notice: </span>
-        To better understand how to tackle the data issues highlighted in this report, explore our comprehensive <a href="https://deci.ai/course/profiling-computer-vision-datasets-overview/">course</a> on analyzing computer vision datasets."
+        To better understand how to tackle the data issues highlighted in this report, explore our comprehensive <a href="https://deci.ai/course/profiling-computer-vision-datasets-overview/?utm_campaign[…]=DG-PDF-report&utm_medium=DG-repo&utm_content=DG-Report-to-course">course</a> on analyzing computer vision datasets.
     </div>
 </body>
 </html>

src/data_gradients/config/data/questions.py

@@ -1,13 +1,7 @@
 from dataclasses import dataclass
 from typing import Dict, Any, Optional, List
 
-
-def text_to_blue(text: str) -> str:
-    return f"\033[34;1m{text}\033[0m"
-
-
-def text_to_yellow(text: str):
-    return f"\033[33;1m{text}\033[0m"
+from data_gradients.utils.utils import text_to_blue, text_to_yellow
 
 
 @dataclass

src/data_gradients/managers/abstract_manager.py

@@ -10,6 +10,7 @@
 from data_gradients.feature_extractors import AbstractFeatureExtractor
 from data_gradients.batch_processors.base import BatchProcessor
 from data_gradients.feature_extractors.common import SummaryStats
+from data_gradients.utils.utils import print_in_box
 from data_gradients.visualize.seaborn_renderer import SeabornRenderer
 from data_gradients.utils.pdf_writer import ResultsContainer, Section, FeatureSummary
 from data_gradients.utils.summary_writer import SummaryWriter
@@ -98,6 +99,9 @@ def execute(self):
             f"  - feature extractor list: {self.grouped_feature_extractors}"
         )
 
+        print_in_box("To better understand how to tackle the data issues highlighted in this report, explore our comprehensive course on analyzing "
+                     "computer vision datasets. click here: https://hubs.ly/Q01XpHBT0")
+
         datasets_tqdm = tqdm(
             zip_longest(self.train_iter, self.val_iter, fillvalue=None),
             desc="Analyzing... ",

src/data_gradients/utils/utils.py

@@ -77,3 +77,56 @@ def safe_json_load(path: str) -> Dict:
             return json.load(f)
     except json.decoder.JSONDecodeError:
         return {}
+
+
+def text_to_blue(text: str) -> str:
+    return f"\033[34;1m{text}\033[0m"
+
+
+def text_to_yellow(text: str):
+    return f"\033[33;1m{text}\033[0m"
+
+
+def break_text(text: str, line_length: int):
+    lines = []
+    words = text.split()
+    current_line = []
+    current_length = 0
+
+    for word in words:
+        word_length = len(word)
+
+        if current_length + len(current_line) + word_length <= line_length:
+            current_line.append(word)
+            current_length += word_length
+        else:
+            lines.append(' '.join(current_line))
+            current_line = [word]
+            current_length = word_length
+
+    if current_line:
+        lines.append(' '.join(current_line))
+
+    # Add spaces to the end of each line to make them equal in length
+    for i in range(len(lines)):
+        spaces_needed = line_length - len(lines[i])
+        lines[i] += ' ' * spaces_needed
+
+    return lines
+
+
+def print_in_box(text_lines: str, box_size: int = 70):
+    left = text_to_blue("║  ")
+    right = text_to_blue("  ║")
+    bottom_left = text_to_blue("╚")
+    top_bottom = text_to_blue("═")
+    top_left = text_to_blue("╔")
+    top_right = text_to_blue("╗")
+    bottom_right = text_to_blue("╝")
+
+    lines = break_text(text_lines, box_size)
+    top_bottom = top_bottom * (box_size + 4)
+    print(top_left + top_bottom + top_right)
+    for text in lines:
+        print(left + text + right)
+    print(bottom_left + top_bottom +bottom_right)