modify app.py

.gitignore

@@ -0,0 +1,129 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
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+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/

app.py

@@ -1,7 +1,140 @@
+import torch
+
+# usersim_path_shoes = "http://www.dcs.gla.ac.uk/~craigm/fcrs/model_checkpoints/caption_model_shoes"
+# usersim_path_dresses = "http://www.dcs.gla.ac.uk/~craigm/fcrs/captioners/dresses_cap_caption_models"
+
+drive_path = '/content/drive/MyDrive/Datasets/mmir_usersim_resources/'
+
+data_type= ["shoes", "dresses", "shirts", "tops&tees"]
+
+usersim_path_shoes = drive_path + "checkpoints_usersim/shoes"
+usersim_path_dresses = drive_path + "checkpoints_usersim/dresses"
+usersim_path_shirts = drive_path + "checkpoints_usersim/shirts"
+usersim_path_topstees = drive_path + "checkpoints_usersim/topstees"
+usersim_path = [usersim_path_shoes, usersim_path_dresses, usersim_path_shirts, usersim_path_topstees]
+
+import captioning.captioner as captioner
+image_feat_params = {'model':'resnet101','model_root':drive_path + 'imagenet_weights','att_size':7}
+# image_feat_params = {'model':'resnet101','model_root':'','att_size':7}
+
+captioner_relative_shoes = captioner.Captioner(is_relative= True, model_path= usersim_path[0], image_feat_params=image_feat_params, data_type=data_type[0], load_resnet=True)
+captioner_relative_dresses = captioner.Captioner(is_relative= True, model_path= usersim_path[1], image_feat_params=image_feat_params, data_type=data_type[1], load_resnet=True)
+captioner_relative_shirts = captioner.Captioner(is_relative= True, model_path= usersim_path[2], image_feat_params=image_feat_params, data_type=data_type[2], load_resnet=True)
+captioner_relative_topstees = captioner.Captioner(is_relative= True, model_path= usersim_path[3], image_feat_params=image_feat_params, data_type=data_type[3], load_resnet=True)
+
+def generate_sentence_shoes(image_path_1, image_path_2):
+    fc_feat, att_feat = captioner_relative_shoes.get_img_feat(image_path_1)
+    fc_feat_ref, att_feat_ref = captioner_relative_shoes.get_img_feat(image_path_2)
+
+    fc_feat = torch.unsqueeze(fc_feat, dim=0)
+    att_feat = torch.unsqueeze(att_feat, dim=0)
+    fc_feat_ref = torch.unsqueeze(fc_feat_ref, dim=0)
+    att_feat_ref = torch.unsqueeze(att_feat_ref, dim=0)
+
+    seq, sents = captioner_relative_shoes.gen_caption_from_feat((fc_feat,att_feat), (fc_feat_ref,att_feat_ref))
+
+    sentence = sents[0]
+    return sentence
+
+def generate_sentence_dresses(image_path_1, image_path_2):
+    fc_feat, att_feat = captioner_relative_dresses.get_img_feat(image_path_1)
+    fc_feat_ref, att_feat_ref = captioner_relative_dresses.get_img_feat(image_path_2)
+
+    fc_feat = torch.unsqueeze(fc_feat, dim=0)
+    att_feat = torch.unsqueeze(att_feat, dim=0)
+    fc_feat_ref = torch.unsqueeze(fc_feat_ref, dim=0)
+    att_feat_ref = torch.unsqueeze(att_feat_ref, dim=0)
+
+    seq, sents = captioner_relative_dresses.gen_caption_from_feat((fc_feat,att_feat), (fc_feat_ref,att_feat_ref))
+
+    sentence = sents[0]
+    return sentence
+
+def generate_sentence_shirts(image_path_1, image_path_2):
+    fc_feat, att_feat = captioner_relative_shirts.get_img_feat(image_path_1)
+    fc_feat_ref, att_feat_ref = captioner_relative_shirts.get_img_feat(image_path_2)
+
+    fc_feat = torch.unsqueeze(fc_feat, dim=0)
+    att_feat = torch.unsqueeze(att_feat, dim=0)
+    fc_feat_ref = torch.unsqueeze(fc_feat_ref, dim=0)
+    att_feat_ref = torch.unsqueeze(att_feat_ref, dim=0)
+
+    seq, sents = captioner_relative_shirts.gen_caption_from_feat((fc_feat,att_feat), (fc_feat_ref,att_feat_ref))
+
+    sentence = sents[0]
+    return sentence
+
+def generate_sentence_topstees(image_path_1, image_path_2):
+    fc_feat, att_feat = captioner_relative_topstees.get_img_feat(image_path_1)
+    fc_feat_ref, att_feat_ref = captioner_relative_topstees.get_img_feat(image_path_2)
+
+    fc_feat = torch.unsqueeze(fc_feat, dim=0)
+    att_feat = torch.unsqueeze(att_feat, dim=0)
+    fc_feat_ref = torch.unsqueeze(fc_feat_ref, dim=0)
+    att_feat_ref = torch.unsqueeze(att_feat_ref, dim=0)
+
+    seq, sents = captioner_relative_topstees.gen_caption_from_feat((fc_feat,att_feat), (fc_feat_ref,att_feat_ref))
+
+    sentence = sents[0]
+    return sentence
+
+import numpy as np
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+examples_shoes = [["images/shoes/img_womens_athletic_shoes_1223.jpg", "images/shoes/img_womens_athletic_shoes_830.jpg"],
+            ["images/shoes/img_womens_athletic_shoes_830.jpg", "images/shoes/img_womens_athletic_shoes_1223.jpg"],
+            ["images/shoes/img_womens_high_heels_559.jpg", "images/shoes/img_womens_high_heels_690.jpg"],
+            ["images/shoes/img_womens_high_heels_690.jpg", "images/shoes/img_womens_high_heels_559.jpg"]]
+
+examples_dresses = [["images/dresses/B007UZSPC8.jpg", "images/dresses/B006MPVW4U.jpg"],
+                    ["images/dresses/B005KMQQFQ.jpg", "images/dresses/B005QYY5W4.jpg"],
+                    ["images/dresses/B005OBAGD6.jpg", "images/dresses/B006U07GW4.jpg"],
+                    ["images/dresses/B0047Y0K0U.jpg", "images/dresses/B006TAM4CW.jpg"]]
+examples_shirts = [["images/shirts/B00305G9I4.jpg", "images/shirts/B005BLUUJY.jpg"],
+                   ["images/shirts/B004WSVYX8.jpg", "images/shirts/B008TP27PY.jpg"],
+                   ["images/shirts/B003INE0Q6.jpg", "images/shirts/B0051D0X2Q.jpg"],
+                   ["images/shirts/B00EZUKCCM.jpg", "images/shirts/B00B88ZKXA.jpg"]]
+examples_topstees = [["images/topstees/B0082993AO.jpg", "images/topstees/B008293HO2.jpg"],
+                     ["images/topstees/B006YN4J2C.jpg", "images/topstees/B0035EPUBW.jpg"],
+                     ["images/topstees/B00B5SKOMU.jpg", "images/topstees/B004H3XMYM.jpg"],
+                     ["images/topstees/B008DVXGO0.jpg", "images/topstees/B008JYNN30.jpg"]
+                     ]
+
+with gr.Blocks() as demo:
+    gr.Markdown("Relative Captioning for Fashion.")
+    with gr.Tab("Shoes"):
+        with gr.Row():
+          target_shoes = gr.Image(source="upload", type="filepath", label="Target Image")
+          candidate_shoes = gr.Image(source="upload", type="filepath", label="Candidate Image")
+          output_text_shoes = gr.Textbox(label="Generated Sentence")
+        shoes_btn = gr.Button("Generate")
+        gr.Examples(examples_shoes, inputs=[target_shoes, candidate_shoes])
+    with gr.Tab("Dresses"):
+        with gr.Row():
+          target_dresses = gr.Image(source="upload", type="filepath", label="Target Image")
+          candidate_dresses = gr.Image(source="upload", type="filepath", label="Candidate Image")
+          output_text_dresses = gr.Textbox(label="Generated Sentence")
+        dresses_btn = gr.Button("Generate")
+        gr.Examples(examples_dresses, inputs=[target_dresses, candidate_dresses])
+    with gr.Tab("Shirts"):
+        with gr.Row():
+          target_shirts = gr.Image(source="upload", type="filepath", label="Target Image")
+          candidate_shirts = gr.Image(source="upload", type="filepath", label="Candidate Image")
+          output_text_shirts = gr.Textbox(label="Generated Sentence")
+        shirts_btn = gr.Button("Generate")
+        gr.Examples(examples_shirts, inputs=[target_shirts, candidate_shirts])
+    with gr.Tab("Tops&Tees"):
+        with gr.Row():
+          target_topstees = gr.Image(source="upload", type="filepath", label="Target Image")
+          candidate_topstees = gr.Image(source="upload", type="filepath", label="Candidate Image")
+          output_text_topstees = gr.Textbox(label="Generated Sentence")
+        topstees_btn = gr.Button("Generate")
+        gr.Examples(examples_topstees, inputs=[target_topstees, candidate_topstees])
+
+    shoes_btn.click(generate_sentence_shoes, inputs=[target_shoes, candidate_shoes], outputs=output_text_shoes)
+    dresses_btn.click(generate_sentence_dresses, inputs=[target_dresses, candidate_dresses], outputs=output_text_dresses)
+    shirts_btn.click(generate_sentence_shirts, inputs=[target_shirts, candidate_shirts], outputs=output_text_shirts)
+    topstees_btn.click(generate_sentence_topstees, inputs=[target_topstees, candidate_topstees], outputs=output_text_topstees)
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+demo.queue(concurrency_count=3)
+demo.launch()