Update README.md

README.md

@@ -81,7 +81,7 @@ import fiftyone.utils.huggingface as fouh
 
 # Load the dataset
 # Note: other available arguments include 'max_samples', etc
-dataset = fouh.load_from_hub("harpreetsahota/Coursera_homework_dataset_train")
+dataset = fouh.load_from_hub("Voxel51/Coursera_homework_dataset_train")
 
 # Launch the App
 session = fo.launch_app(dataset)
@@ -97,28 +97,25 @@ This dataset is a modified subset of the [LVIS dataset](https://www.lvisdataset.
 The dataset here only contains detections, some of which have been artificially perturbed and altered to demonstrate data centric AI techniques and methodologies for the course.
 
 This dataset has the following labels: 
-
- - 'jacket'
- - 'coat'
- - 'jean'
- - 'trousers'
- - 'short_pants'
- - 'trash_can'
- - 'bucket'
- - 'flowerpot'
- - 'helmet'
- - 'baseball_cap'
- - 'hat'
- - 'sunglasses'
- - 'goggles'
- - 'doughnut'
- - 'pastry'
- - 'onion'
- - 'tomato'
-
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
+ - 'bolt'
+ - 'knob'
+ - 'tag'
+ - 'button'
+ - 'bottle_cap'
+ - 'belt'
+ - 'strap'
+ - 'necktie'
+ - 'shirt'
+ - 'sweater'
+ - 'streetlight'
+ - 'pole'
+ - 'reflector'
+ - 'headlight'
+ - 'taillight'
+ - 'traffic_light'
+ - 'rearview_mirror'
+
+### Dataset Sources
 
 - **Repository:** https://www.lvisdataset.org/
 - **Paper:** https://arxiv.org/abs/1908.03195
@@ -134,15 +131,15 @@ Each image in the dataset comes with detailed annotations in FiftyOne detection
 
 ```python
 <Detection: {
-    'id': '66a2f24cce2f9d11d98d39f3',
+    'id': '66a2f24cce2f9d11d98d3a21',
     'attributes': {},
     'tags': [],
-    'label': 'trousers',
+    'label': 'shirt',
     'bounding_box': [
-        0.5562343750000001,
-        0.4614166666666667,
-        0.1974375,
-        0.29300000000000004,
+        0.25414,
+        0.35845238095238097,
+        0.041960000000000004,
+        0.051011904761904765,
     ],
     'mask': None,
     'confidence': None,
@@ -154,7 +151,7 @@ Each image in the dataset comes with detailed annotations in FiftyOne detection
 
 ### Curation Rationale
 
-The selected labels for this dataset is due to the fact that these objects can be confusing to a model. Thus, making them a great choice for demonstrating data centric AI techniques.
+The selected labels for this dataset is because these objects can be confusing to a model. Thus, making them a great choice for demonstrating data centric AI techniques.
 
 ### Source Data
 
@@ -162,8 +159,6 @@ This is a subset of the [LVIS dataset.](https://www.lvisdataset.org/)
 
 ## Citation
 
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-
 **BibTeX:**
 
 ```bibtex