Upload load.py

load.py

@@ -1,100 +1,54 @@
 import json
-import sys
 import os
+import time
 import urllib.request as ureq
-import pdb
 
-download=1 # 0 if images are already downloaded
-
-###############################################################
-######################### load dataset json file ###############
-################################################################
+def download_image_with_retries(url, output_file, max_retries=3, backoff_factor=1):
+    """Attempt to download an image with retries upon failure.
+
+    Args:
+        url (str): The URL of the image to download.
+        output_file (str): The local file path to save the downloaded image.
+        max_retries (int): The maximum number of retry attempts.
+        backoff_factor (float): The factor to calculate the delay between retries.
+    """
+    attempt = 0
+    while attempt < max_retries:
+        try:
+            ureq.urlretrieve(url, output_file)
+            print(f"Successfully downloaded: {output_file}")
+            return True
+        except Exception as e:
+            print(f"Attempt {attempt + 1} failed for {url}: {e}")
+            time.sleep(backoff_factor * (2 ** attempt))
+            attempt += 1
+    print(f"Failed to download {url} after {max_retries} attempts.")
+    return False
+
+def verify_and_download_images(data):
+    """Verify if images are downloaded; if not, download them.
+
+    Args:
+        data (dict): The dataset containing image URLs and additional information.
+    """
+    images_directory = './images'
+    os.makedirs(images_directory, exist_ok=True)
+
+    for key, value in data.items():
+        image_url = value['imageURL']
+        ext = os.path.splitext(image_url)[1]
+        output_file = f'{images_directory}/{key}{ext}'
+
+        if not os.path.exists(output_file):
+            print(f"Image {key}{ext} not found, attempting to download...")
+            if not download_image_with_retries(image_url, output_file):
+                print(f"Warning: Could not download image {image_url}")
+        else:
+            print(f"Image {key}{ext} already exists. No download needed.")
+
+# Load the dataset JSON file
 with open('dataset.json', 'r') as fp:
-        data = json.load(fp)
-
-## dictionary data contains image URL, questions and answers ##
-
-
-
-
-################################################################
-############### Script for downloading images ##################
-################################################################
-## Make a directory images to store all images there ##########
-if download == 1:
-    os.makedirs('./images', exist_ok=True)
-    for k in data.keys():
-        ext=os.path.splitext(data[k]['imageURL'])[1]
-        outputFile='images/%s%s'%(k,ext)
-        #pdb.set_trace()
-        ureq.urlretrieve(data[k]['imageURL'],outputFile)    
-
-
-
-#################################################################
-################### Example of data access #####################
-################################################################
-for k in data.keys():
-    ext=os.path.splitext(data[k]['imageURL'])[1]
-    imageFile='images/%s%s'%(k,ext)
-
-    print('************************')
-    print('Image file: %s'%(imageFile))
-    print('List of questions:')
-    print(data[k]['questions'])
-    print('List of corresponding answers:')
-    print(data[k]['answers'])
-    print('Use this image as training (1), validation (2) or testing (3): %s'%(data[k]['split']))
-    print('*************************')
-
-
-
-
-
-######################################################################
-########################### Get dataset stats ########################
-######################################################################
-genSet=set()
-for k in data.keys():
-    genSet.add(data[k]['genre'])
-
-
-
-numImages=len(data.keys())
-numQApairs=0
-numWordsInQuestions=0
-numWordsInAnswers=0
-numQuestionsPerImage=0
-ANS=set() # Set of unique answers
-authorSet=set()
-bookSet=set()
-
-
-for imgId in data.keys():
-    numQApairs = numQApairs+len(data[imgId]['questions'])
-    numQuestionsPerImage = numQuestionsPerImage + len(data[imgId]['questions'])
-    authorSet.add(data[imgId]['authorName'])
-    bookSet.add(data[imgId]['title'])
-
-    for qno in range(len(data[imgId]['questions'])):
-        ques=data[imgId]['questions'][qno]
-        numWordsInQuestions = numWordsInQuestions+len(ques.split())
-    for ano in range(len(data[imgId]['answers'])):
-        ans=data[imgId]['answers'][ano]
-        ANS.add(ans)
-        numWordsInAnswers = numWordsInAnswers+len(str(ans).split())
-
-
-
-print("--------------------------------")
-print("Number of Images: %d" %(numImages))
-print("Number of QA pairs: %d" %(numQApairs))
-print("Number of unique author: %d" %(len(authorSet)))
-print("Number of unique title: %d" %(len(bookSet)))
-print("Number of unique answers: %d" %(len(ANS)))
-print("Number of unique genre: %d" %(len(genSet)))
-print("Average question length (in words): %.2f" %(float(numWordsInQuestions)/float(numQApairs)))
-print("Average answer length (in words): %.2f" %(float(numWordsInAnswers)/float(numQApairs)))
-print("Average number of questions per image: %.2f" %(float(numQuestionsPerImage)/float(numImages)))
-print("--------------------------------")
+    data = json.load(fp)
 
+# Check and download images as necessary
+verify_and_download_images(data)