Spaces:
Runtime error
Runtime error
paul hilders
commited on
Commit
·
9775911
1
Parent(s):
9ee9e02
Update descriptions again
Browse files
app.py
CHANGED
@@ -62,7 +62,7 @@ outputs = [gr.inputs.Image(type='pil', label="Output Image"), "highlight"]
|
|
62 |
|
63 |
description = """A demonstration based on the Generic Attention-model Explainability method for Interpreting Bi-Modal
|
64 |
Transformers by Chefer et al. (2021): https://github.com/hila-chefer/Transformer-MM-Explainability.
|
65 |
-
|
66 |
This demo shows attributions scores on both the image and the text input when presented CLIP with a
|
67 |
<text,image> pair. Attributions are computed as Gradient-weighted Attention Rollout (Chefer et al.,
|
68 |
2021), and can be thought of as an estimate of the effective attention CLIP pays to its input when
|
@@ -125,11 +125,14 @@ inputs_NER = [input_img_NER, input_txt_NER]
|
|
125 |
|
126 |
outputs_NER = ["highlight", gr.Gallery(type='pil', label="NER Entity explanations")]
|
127 |
|
|
|
|
|
128 |
|
129 |
iface_NER = gr.Interface(fn=NER_demo,
|
130 |
inputs=inputs_NER,
|
131 |
outputs=outputs_NER,
|
132 |
title="Named Entity Grounding explainability using CLIP",
|
|
|
133 |
examples=[["example_images/London.png", "In this image we see Big Ben and the London Eye, on both sides of the river Thames."]],
|
134 |
cache_examples=False)
|
135 |
|
|
|
62 |
|
63 |
description = """A demonstration based on the Generic Attention-model Explainability method for Interpreting Bi-Modal
|
64 |
Transformers by Chefer et al. (2021): https://github.com/hila-chefer/Transformer-MM-Explainability.
|
65 |
+
<br> <br>
|
66 |
This demo shows attributions scores on both the image and the text input when presented CLIP with a
|
67 |
<text,image> pair. Attributions are computed as Gradient-weighted Attention Rollout (Chefer et al.,
|
68 |
2021), and can be thought of as an estimate of the effective attention CLIP pays to its input when
|
|
|
125 |
|
126 |
outputs_NER = ["highlight", gr.Gallery(type='pil', label="NER Entity explanations")]
|
127 |
|
128 |
+
description_NER = """Automatically generated CLIP grounding explanations for
|
129 |
+
named entities, retrieved from the spacy NER model."""
|
130 |
|
131 |
iface_NER = gr.Interface(fn=NER_demo,
|
132 |
inputs=inputs_NER,
|
133 |
outputs=outputs_NER,
|
134 |
title="Named Entity Grounding explainability using CLIP",
|
135 |
+
description=description_NER,
|
136 |
examples=[["example_images/London.png", "In this image we see Big Ben and the London Eye, on both sides of the river Thames."]],
|
137 |
cache_examples=False)
|
138 |
|