Uploading Trashify box detection model app.py

README.md

@@ -22,14 +22,7 @@ If `trash`, `hand`, `bin` all detected = +1 point.
 
 All Trashify models are trained on a custom hand-labelled dataset of people picking up trash and placing it in a bin.
 
-The dataset can be found on Hugging Face as [`HimanshuGoyal2004/trashify_manual_labelled_images`](https://huggingface.co/datasets/HimanshuGoyal2004/trashify_manual_labelled_images).
-
-## Demos
-
-* [V1](https://huggingface.co/spaces/HimanshuGoyal2004/trashify_demo_v1) = Fine-tuned [Conditional DETR](https://huggingface.co/docs/transformers/en/model_doc/conditional_detr) model trained *without* data augmentation.
-* [V2](https://huggingface.co/spaces/HimanshuGoyal2004/trashify_demo_v2) = Fine-tuned Conditional DETR model trained *with* data augmentation.
-* [V3](https://huggingface.co/spaces/HimanshuGoyal2004/trashify_demo_v3) = Fine-tuned Conditional DETR model trained *with* data augmentation (same as V2) with an NMS (Non Maximum Suppression) post-processing step.
-* [V4](https://huggingface.co/spaces/HimanshuGoyal2004/trashify_demo_v4) = Fine-tuned [RT-DETRv2](https://huggingface.co/docs/transformers/main/en/model_doc/rt_detr_v2) model trained *without* data augmentation or NMS post-processing (current best mAP).
+The dataset can be found on Hugging Face as [`mrdbourke/trashify_manual_labelled_images`](https://huggingface.co/datasets/HimanshuGoyal2004/trashify_manual_labelled_images).
 
 ## Learn more
 

app.py

@@ -142,11 +142,11 @@ def predict_on_image(image, conf_threshold):
 description = """
 Help clean up your local area! Upload an image and get +1 if there is all of the following items detected: trash, bin, hand.
 
-Model is a fine-tuned version of [RT-DETRv2](https://huggingface.co/docs/transformers/main/en/model_doc/rt_detr_v2#transformers.RTDetrV2Config) on the [Trashify dataset](https://huggingface.co/datasets/HimanshuGoyal2004/trashify_manual_labelled_images).
+Model is a fine-tuned version of [RT-DETRv2](https://huggingface.co/docs/transformers/main/en/model_doc/rt_detr_v2#transformers.RTDetrV2Config) on the [Trashify dataset](https://huggingface.co/datasets/mrdbourke/trashify_manual_labelled_images).
 
-See the full data loading and training code on [learnhuggingface.com](https://www.learnhuggingface.com/notebooks/hugging_face_object_detection_tutorial).
+See the full data loading and training code on this [google colab notebook](https://colab.research.google.com/drive/1BBMETl2eSEhcj0oTvuOq4mg4Doocibth?usp=sharing).
 
-This version is v4 because the first three versions were using a different model and did not perform as well, see the [README](https://huggingface.co/spaces/HimanshuGoyal2004/trashify_demo_v4/blob/main/README.md) for more.
+See the [README](https://huggingface.co/spaces/HimanshuGoyal2004/trashify_demo_v4/blob/main/README.md) for more.
 """
 
 # Create the Gradio interface to accept an image and confidence threshold and return an image with drawn prediction boxes
@@ -160,10 +160,10 @@ demo = gr.Interface(
         gr.Image(type="pil", label="Image Output"),
         gr.Text(label="Text Output")
     ],
-    title="🚮 Trashify Object Detection Demo V4",
+    title="🚮 Trashify Object Detection Demo",
     description=description,
     # Examples come in the form of a list of lists, where each inner list contains elements to prefill the `inputs` parameter with
-    # See where the examples originate from here: https://huggingface.co/datasets/HimanshuGoyal2004/trashify_examples/
+    # See where the examples originate from here: https://huggingface.co/datasets/mrdbourke/trashify_examples/
     examples=[
         ["trashify_examples/trashify_example_1.jpeg", 0.3],
         ["trashify_examples/trashify_example_2.jpeg", 0.3],