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Added examples

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Files changed (18) hide show
  1. app.py +11 -19
  2. imgs/examples/Animalia_Arthropoda_Malacostraca_Decapoda_Ocypodidae_Ocypode_quadrata/0b9cc264-a2ba-44bd-8e41-0d01a6edd1e8.jpg +3 -0
  3. imgs/examples/Animalia_Arthropoda_Malacostraca_Decapoda_Ocypodidae_Ocypode_quadrata/277303_38.72364_-75.07749.jpg +3 -0
  4. imgs/examples/Animalia_Chordata_Aves_Charadriiformes_Laridae_Larus_marinus/80645_39.76079_-74.10316.jpg +3 -0
  5. imgs/examples/Animalia_Chordata_Aves_Charadriiformes_Laridae_Larus_marinus/cc1ebaf9-899d-49f2-81c8-d452249a8087.jpg +3 -0
  6. imgs/examples/Animalia_Chordata_Mammalia_Carnivora_Canidae_Canis_aureus/1528408_13.00422_80.23033.jpg +3 -0
  7. imgs/examples/Animalia_Chordata_Mammalia_Carnivora_Canidae_Canis_aureus/37faabd2-a613-4461-b27e-82fe5955ecaf.jpg +3 -0
  8. imgs/examples/Animalia_Chordata_Mammalia_Carnivora_Canidae_Urocyon_littoralis/0cbdfbf2-6cfe-4d61-9602-c949f24d0293.jpg +3 -0
  9. imgs/examples/Animalia_Chordata_Mammalia_Carnivora_Canidae_Urocyon_littoralis/304160_34.0144_-119.54417.jpg +3 -0
  10. imgs/examples/Animalia_Chordata_Mammalia_Carnivora_Phocidae_Mirounga_angustirostris/27423_35.64005_-121.17595.jpg +3 -0
  11. imgs/examples/Animalia_Chordata_Mammalia_Carnivora_Phocidae_Mirounga_angustirostris/3aac526d-c921-452a-af6a-cb4f2f52e2c4.jpg +3 -0
  12. imgs/examples/Animalia_Chordata_Mammalia_Rodentia_Caviidae_Hydrochoerus_hydrochaeris/1b8064f8-7deb-4b30-98cd-69da98ba6a3d.jpg +3 -0
  13. imgs/examples/Animalia_Chordata_Mammalia_Rodentia_Caviidae_Hydrochoerus_hydrochaeris/28871_-12.80255_-69.29999.jpg +3 -0
  14. imgs/examples/Animalia_Chordata_Mammalia_Rodentia_Sciuridae_Marmota_marmota/327e1f07-692b-4140-8a3e-bd098bc064ff.jpg +3 -0
  15. imgs/examples/Animalia_Chordata_Mammalia_Rodentia_Sciuridae_Marmota_marmota/388246_45.49036_7.14796.jpg +3 -0
  16. imgs/examples/Animalia_Chordata_Reptilia_Squamata_Varanidae_Varanus_salvator/410613_5.35573_100.28948.jpg +3 -0
  17. imgs/examples/Animalia_Chordata_Reptilia_Squamata_Varanidae_Varanus_salvator/461d8e6c-0e66-4acc-8ecd-bfd9c218bc14.jpg +3 -0
  18. imgs/examples/metadata.json +367 -0
app.py CHANGED
@@ -158,21 +158,13 @@ model.eval()
158
  # Gradio
159
  examples = [
160
  [
161
- "Where can the driver see the car speed in this image? Please output segmentation mask.",
162
- "./imgs/example1.jpg",
163
- ],
164
- [
165
- "Can you segment the food that tastes spicy and hot?",
166
- "./imgs/example2.jpg",
167
- ],
168
  [
169
- "Assuming you are an autonomous driving robot, what part of the diagram would you manipulate to control the direction of travel? Please output segmentation mask and explain why.",
170
- "./imgs/example1.jpg",
171
- ],
172
- [
173
- "What can make the woman stand higher? Please output segmentation mask and explain why.",
174
- "./imgs/stand_higher.jpg",
175
- ],
176
  ]
177
  output_labels = ["Segmentation Output"]
178
 
@@ -185,10 +177,10 @@ If multiple users are using it at the same time, they will enter a queue, which
185
  **Note**: **Different prompts can lead to significantly varied results**. \n
186
  **Note**: Please try to **standardize** your input text prompts to **avoid ambiguity**, and also pay attention to whether the **punctuations** of the input are correct. \n
187
  **Usage**: <br>
188
- &ensp;(1) To let LISA **segment something**, input prompt like: "Can you segment xxx in this image?", "What is xxx in this image? Please output segmentation mask."; <br>
189
- &ensp;(2) To let LISA **output an explanation**, input prompt like: "What is xxx in this image? Please output segmentation mask and explain why."; <br>
190
- &ensp;(3) To obtain **solely language output**, you can input like what you should do in current multi-modal LLM (e.g., LLaVA). <br>
191
- Hope you can enjoy our work!
192
  </font>
193
  """
194
 
@@ -356,7 +348,7 @@ demo = gr.Interface(
356
  title=title,
357
  description=description,
358
  article=article,
359
- examples=None,
360
  allow_flagging="auto",
361
  )
362
 
 
158
  # Gradio
159
  examples = [
160
  [
161
+ "Where can I find the shore birds (Animalia Chordata Aves Charadriiformes Laridae Larus marinus) in this image? Please output segmentation mask and explain why.",
162
+ "./imgs/examples/Animalia_Chordata_Aves_Charadriiformes_Laridae_Larus_marinus/80645_39.76079_-74.10316.jpg",
163
+ ],
 
 
 
 
164
  [
165
+ "Where can I find the capybaras (Animalia Chordata Mammalia Rodentia Caviidae Hydrochoerus hydrochaeris) in this image? Please output segmentation mask.",
166
+ "./imgs/examples/Animalia_Chordata_Mammalia_Rodentia_Caviidae_Hydrochoerus_hydrochaeris/28871_-12.80255_-69.29999.jpg",
167
+ ],
 
 
 
 
168
  ]
169
  output_labels = ["Segmentation Output"]
170
 
 
177
  **Note**: **Different prompts can lead to significantly varied results**. \n
178
  **Note**: Please try to **standardize** your input text prompts to **avoid ambiguity**, and also pay attention to whether the **punctuations** of the input are correct. \n
179
  **Usage**: <br>
180
+ &ensp;(1) To let LISA-AVS **segment something**, input prompt like: "Where can I find the <Common Name> (<Full Taxonomy Name>) in this image? Please output segmentation mask."; <br>
181
+ &ensp;(2) To let LISA-AVS **output an explanation**, input prompt like: "Where can I find the <Common Name> (<Full Taxonomy Name>) in this image? Please output segmentation mask and explain why."; <br>
182
+ &ensp;(3) To obtain **solely language output**, you can input like what you should do in current multi-modal LLM (e.g., LLaVA), like: "Where can I find the <Common Name> (<Full Taxonomy Name>) in this image?" <br>
183
+
184
  </font>
185
  """
186
 
 
348
  title=title,
349
  description=description,
350
  article=article,
351
+ examples=examples,
352
  allow_flagging="auto",
353
  )
354
 
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