Merge branch 'main' of https://huggingface.co/datasets/faridlab/deepaction_v1

README.md

@@ -1,5 +1,4 @@
 ---
-license: openrail
 viewer: false
 tags:
 - deepfakes
@@ -192,7 +191,7 @@ Included below are example videos generated using the prompt "a person taking a
 
 ## Licensing
 
-TBD, will be provided by pcounsel
+The AI-generated videos (folders BDAnimateDiffLightning, CogVideoX5B, RunwayML, StableDiffusion, Veo, and VideoPoet) are released under <a href='https://creativecommons.org/licenses/by/4.0/deed.en'>the CC BY 4.0 license</a>. The real videos (folder Pexels) are released under <a href='https://www.pexels.com/license/'>the Pexels license</a>.
 
 <br>
 

deepaction_v1.py

@@ -18,6 +18,8 @@ _HOMEPAGE = "https://huggingface.co/datasets/faridlab/deepaction_v1"
 
 _LICENSE = "TBD"
 
+SUPPORTED = ["VideoPoet", "BDAnimateDiffLightning", "CogVideoX5B", "Pexels", "RunwayML", "StableDiffusion"] # todo add veo
+
 class DeepActionV1(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.0.0")
 
@@ -26,7 +28,7 @@ class DeepActionV1(datasets.GeneratorBasedBuilder):
             description=_DESCRIPTION,
             features=datasets.Features({
                 "video": datasets.Video(),
-                "label": datasets.ClassLabel(names=["VideoPoet", "BDAnimateDiffLightning", "CogVideoX5B", "Pexels", "RunwayML", "StableDiffusion", "Veo"]),  # Add all category names
+                "label": datasets.ClassLabel(names=SUPPORTED),  # Add all category names
             }),
             supervised_keys=("video", "label"),
             homepage=_HOMEPAGE,
@@ -35,8 +37,21 @@ class DeepActionV1(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        url = "https://huggingface.co/datasets/faridlab/deepaction_v1/resolve/main/data.zip"
-        data_dir = dl_manager.download_and_extract(url)
+        urls = []
+        base_url = "https://huggingface.co/datasets/faridlab/deepaction_v1/resolve/main/"
+
+        for engine in SUPPORTED:
+            for i in list(range(95)) + list(range(99, 104)):
+                if engine in ["Pexels", "Veo"]:
+                    urls.append(os.path.join(base_url, engine, "{}".format(i), "a.mp4"))
+                elif engine in ["VideoPoet"]:
+                    for vid_file in ["a.mp4", "b.mp4", "c.mp4", "d.mp4"]:
+                        urls.append(os.path.join(base_url, engine, "{}".format(i), vid_file))
+                else:
+                    for vid_file in ["a.mp4", "b.mp4", "c.mp4", "d.mp4", "e.mp4"]:
+                        urls.append(os.path.join(base_url, engine, "{}".format(i), vid_file))
+        
+        data_dir = dl_manager.download_and_extract(urls)
 
         return [
             datasets.SplitGenerator(
@@ -46,12 +61,11 @@ class DeepActionV1(datasets.GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, data_dir):
-        label_names = os.listdir(data_dir)
-        for label in label_names:
-            label_dir = os.path.join(data_dir, label)
-            if os.path.isdir(label_dir):
-                for subfolder in os.listdir(label_dir):
-                    subfolder_path = os.path.join(label_dir, subfolder)
+        for label in os.listdir(data_dir):
+            label_path = os.path.join(data_dir, label)
+            if os.path.isdir(label_path):
+                for subfolder in os.listdir(label_path):
+                    subfolder_path = os.path.join(label_path, subfolder)
                     if os.path.isdir(subfolder_path):
                         for video_file in os.listdir(subfolder_path):
                             if video_file.endswith(".mp4"):