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TGIF.py

@@ -3,6 +3,7 @@
 
 import csv
 import datasets
+import os
 
 _CITATION = """
 @InProceedings{tgif-cvpr2016,
@@ -24,7 +25,7 @@ and three sentences per GIF for the test split. The dataset shall be used to eva
 
 _URL_BASE = "http://raingo.github.io/TGIF-Release/"
 
-_DL_URL = "https://huggingface.co/datasets/Leyo/TGIF/resolve/main/data.tar.gz"
+_DL_URL = "https://github.com/raingo/TGIF-Release/archive/master.zip"
 
 
 class TGIFConfig(datasets.BuilderConfig):
@@ -47,7 +48,7 @@ class TGIF(datasets.GeneratorBasedBuilder):
             description=_DESCRIPTION,
             features=datasets.Features(
                 {
-                    "video_path": datasets.Value("string"),
+                    "path": datasets.Value("string"),
                     "captions": datasets.features.Sequence(datasets.Value("string"))
                 }
             ),
@@ -57,13 +58,16 @@ class TGIF(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        archive_path = dl_manager.download(_DL_URL)
+        archive_path = dl_manager.download_and_extract(_DL_URL)
+        archive_data_path = archive_path + "data/splits/"
+        infos_file = archive_path + "data/tgif-v1.0.tsv"
+        
         train_splits = [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "files": dl_manager.iter_archive(archive_path),
-                    "split": "train"
+                    "split_links_file": os.path.join(archive_data_path, "train.txt"),
+                    "infos_file": infos_file
                 },
             )
         ]
@@ -71,8 +75,8 @@ class TGIF(datasets.GeneratorBasedBuilder):
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
-                    "files": dl_manager.iter_archive(archive_path),
-                    "split": "dev"
+                    "split_links_file": os.path.join(archive_data_path, "dev.txt"),
+                    "infos_file": infos_file
                 },
             )
         ]
@@ -80,36 +84,31 @@ class TGIF(datasets.GeneratorBasedBuilder):
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
-                    "files": dl_manager.iter_archive(archive_path),
-                    "split": "test"
+                    "split_links_file": os.path.join(archive_data_path, "test.txt"),
+                    "infos_file": infos_file
                 },
             )
         ]
         return train_splits + dev_splits + test_splits
 
-    def _generate_examples(self, files, split):
+    def _generate_examples(self, split_links_file, infos_file):
         """This function returns the examples."""
 
         dict = {}
-        for path, f in files:
-            if path.endswith(split + ".txt"):
-                txt_file = f.read().decode("utf-8").split("\n")
-                for line in txt_file:
-                    line = line
+        split_links_file = "/content/TGIF-Release-master/data/splits/test.txt"
+        with open(split_links_file,encoding = "utf-8") as txt_file:
+            for line in txt_file:
+                    line = line[0:-1]
                     dict[line] = []
-        for path, f in files:
-            if path.endswith("tgif-v1.0.tsv"):
-                tsv_file = f.read().decode("utf-8").split("\n")[:-1]
-                tsv_reader = csv.reader(
-                    tsv_file, delimiter="\t", quotechar='"')
-                for idx, (video_path, text) in enumerate(tsv_reader):
-                    try:
-                        dict[video_path].append(text)
-                    except Exception:
-                        pass
-
-        for idx, video_path in enumerate(dict):
-            yield idx, {
-                "video_path": video_path,
-                "captions": dict[video_path],
-            }
+        infos_file = "/content/TGIF-Release-master/data/tgif-v1.0.tsv"
+        with open(infos_file, encoding="utf-8") as tsv_file:
+            tsv_reader = csv.reader(tsv_file, delimiter="\t", quotechar='"' )
+            for idx, (video_link, text) in enumerate(tsv_reader):
+                try:        
+                    dict[video_link].append(text)
+                except Exception:
+                    pass
+                yield idx, {
+                        "path": video_link,
+                        "captions": text,
+                    }