dataset uploaded by roboflow2huggingface package

README.md

@@ -3,12 +3,50 @@ task_categories:
 - object-detection
 tags:
 - roboflow
+- roboflow2huggingface
+
 ---
 
+<div align="center">
+  <img width="640" alt="keremberke/valorant-object-detection" src="https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/thumbnail.jpg">
+</div>
+
+### Dataset Labels
+
+```
+['dropped spike', 'enemy', 'planted spike', 'teammate']
+```
+
+
+### Number of Images
+
+```json
+{'valid': 1983, 'train': 6927, 'test': 988}
+```
+
+
+### How to Use
+
+- Install [datasets](https://pypi.org/project/datasets/):
+
+```bash
+pip install datasets
+```
+
+- Load the dataset:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("keremberke/valorant-object-detection", name="full")
+example = ds['train'][0]
+```
+
 ### Roboflow Dataset Page
-[https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp](https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp?ref=roboflow2huggingface)
+[https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp/dataset/3](https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp/dataset/3?ref=roboflow2huggingface)
 
 ### Citation
+
 ```
 @misc{ valorant-9ufcp_dataset,
     title = { valorant Dataset },
@@ -20,7 +58,7 @@ tags:
     publisher = { Roboflow },
     year = { 2022 },
     month = { nov },
-    note = { visited on 2022-12-28 },
+    note = { visited on 2023-01-27 },
 }
 ```
 

data/test.zip

@@ -1,3 +1,3 @@
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-oid sha256:82692b36ebd88e137f6658741d406055cbfc5b49437377e594fda9f091a45db4
+oid sha256:a57b880df26ec92211f624fe6d557cdc2dce8e77a7e88f28a8e4859f6962a312
 size 24920040

data/train.zip

@@ -1,3 +1,3 @@
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-oid sha256:82d1c04e6797715525399d728abc3caca70112725b497af23706e72bc88195a7
+oid sha256:79d3175f8df25d1ae30af1b1eff874b306cfca2a2cee64835dbb2c39e0d03be1
 size 175503866

data/valid-mini.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b7a747b1af1fb6ccf3f604fb84bc0e4f665252f533c43c556d6e4f6aa464b25c
+size 75235

data/valid.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d68e71188c2825f8f4d627646c56f06b251ce9cd9f095da6da28c3cfe466adc2
+oid sha256:070cd1c8814ebde3d6f165aaa8387a2f08c3314215c2207447061e36152ad7f0
 size 50166533

split_name_to_num_samples.json

@@ -0,0 +1 @@
+{"valid": 1983, "train": 6927, "test": 988}

valorant-object-detection.py

@@ -5,7 +5,7 @@ import os
 import datasets
 
 
-_HOMEPAGE = "https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp"
+_HOMEPAGE = "https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp/dataset/3"
 _LICENSE = "CC BY 4.0"
 _CITATION = """\
 @misc{ valorant-9ufcp_dataset,
@@ -18,21 +18,52 @@ _CITATION = """\
     publisher = { Roboflow },
     year = { 2022 },
     month = { nov },
-    note = { visited on 2022-12-28 },
+    note = { visited on 2023-01-27 },
 }
 """
-_URLS = {
-    "train": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/train.zip",
-    "validation": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/valid.zip",
-    "test": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/test.zip",
-}
-
-_CATEGORIES = ['enemy', 'dropped spike', 'planted spike', 'teammate']
+_CATEGORIES = ['dropped spike', 'enemy', 'planted spike', 'teammate']
 _ANNOTATION_FILENAME = "_annotations.coco.json"
 
 
+class VALORANTOBJECTDETECTIONConfig(datasets.BuilderConfig):
+    """Builder Config for valorant-object-detection"""
+
+    def __init__(self, data_urls, **kwargs):
+        """
+        BuilderConfig for valorant-object-detection.
+
+        Args:
+          data_urls: `dict`, name to url to download the zip file from.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(VALORANTOBJECTDETECTIONConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
+        self.data_urls = data_urls
+
+
 class VALORANTOBJECTDETECTION(datasets.GeneratorBasedBuilder):
+    """valorant-object-detection object detection dataset"""
+
     VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        VALORANTOBJECTDETECTIONConfig(
+            name="full",
+            description="Full version of valorant-object-detection dataset.",
+            data_urls={
+                "train": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/train.zip",
+                "validation": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/valid.zip",
+                "test": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/test.zip",
+            },
+        ),
+        VALORANTOBJECTDETECTIONConfig(
+            name="mini",
+            description="Mini version of valorant-object-detection dataset.",
+            data_urls={
+                "train": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/valid-mini.zip",
+                "validation": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/valid-mini.zip",
+                "test": "https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/data/valid-mini.zip",
+            },
+        )
+    ]
 
     def _info(self):
         features = datasets.Features(
@@ -59,7 +90,7 @@ class VALORANTOBJECTDETECTION(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        data_files = dl_manager.download_and_extract(_URLS)
+        data_files = dl_manager.download_and_extract(self.config.data_urls)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -92,7 +123,7 @@ class VALORANTOBJECTDETECTION(datasets.GeneratorBasedBuilder):
 
         image_id_to_image = {}
         idx = 0
-        
+
         annotation_filepath = os.path.join(folder_dir, _ANNOTATION_FILENAME)
         with open(annotation_filepath, "r") as f:
             annotations = json.load(f)
@@ -100,12 +131,12 @@ class VALORANTOBJECTDETECTION(datasets.GeneratorBasedBuilder):
         image_id_to_annotations = collections.defaultdict(list)
         for annot in annotations["annotations"]:
             image_id_to_annotations[annot["image_id"]].append(annot)
-        image_id_to_image = {annot["file_name"]: annot for annot in annotations["images"]}
+        filename_to_image = {image["file_name"]: image for image in annotations["images"]}
 
         for filename in os.listdir(folder_dir):
             filepath = os.path.join(folder_dir, filename)
-            if filename in image_id_to_image:
-                image = image_id_to_image[filename]
+            if filename in filename_to_image:
+                image = filename_to_image[filename]
                 objects = [
                     process_annot(annot, category_id_to_category) for annot in image_id_to_annotations[image["id"]]
                 ]