marcelcastrobr commited on
Commit
8e0a0ad
1 Parent(s): d98a4ef

fixing deprecated functions in gradio

Browse files
Files changed (3) hide show
  1. README.md +1 -0
  2. app.py +10 -7
  3. requirements.txt +2 -1
README.md CHANGED
@@ -6,6 +6,7 @@ colorTo: pink
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  sdk: gradio
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  app_file: app.py
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  pinned: false
 
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  ---
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  # Configuration
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  sdk: gradio
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  app_file: app.py
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  pinned: false
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+ python_version: 3.10
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  ---
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  # Configuration
app.py CHANGED
@@ -12,12 +12,12 @@ model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
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  processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
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  tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-base-patch32")
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-
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-
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  #Open the precomputed embeddings
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  emb_filename = 'unsplash-25k-photos-embeddings.pkl'
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  with open(emb_filename, 'rb') as fIn:
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- img_names, img_emb = pickle.load(fIn)
 
 
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  def search_text(query, top_k=1):
@@ -41,9 +41,10 @@ def search_text(query, top_k=1):
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  image=[]
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  for hit in hits:
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- print(img_names[hit['corpus_id']])
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  object = Image.open(os.path.join("photos/", img_names[hit['corpus_id']]))
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  image.append(object)
 
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  return image
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@@ -53,11 +54,13 @@ iface = gr.Interface(
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  description = "Gradio Demo fo CLIP model. \n This demo is based on assessment for the 🤗 Huggingface course 2. \n To use it, simply write which image you are looking for. Read more at the links below.",
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  article = "You find more information about this demo on my ✨ github repository [marcelcastrobr](https://github.com/marcelcastrobr/huggingface_course2)",
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  fn=search_text,
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- inputs=[gr.inputs.Textbox(lines=4,
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  label="Write what you are looking for in an image...",
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  placeholder="Text Here..."),
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- gr.inputs.Slider(0, 5, step=1)],
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- outputs=gr.outputs.Carousel(gr.outputs.Image(type="pil"))
 
 
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  ,examples=[[("Dog in the beach"), 2],
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  [("Paris during night."), 1],
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  [("A cute kangaroo"), 5],
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  processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
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  tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-base-patch32")
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  #Open the precomputed embeddings
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  emb_filename = 'unsplash-25k-photos-embeddings.pkl'
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  with open(emb_filename, 'rb') as fIn:
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+ img_names, img_emb = pickle.load(fIn)
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+ #print(f'img_emb: {print(img_emb)}')
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+ #print(f'img_names: {print(img_names)}')
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  def search_text(query, top_k=1):
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  image=[]
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  for hit in hits:
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+ #print(img_names[hit['corpus_id']])
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  object = Image.open(os.path.join("photos/", img_names[hit['corpus_id']]))
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  image.append(object)
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+ #print(f'array length is: {len(image)}')
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  return image
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  description = "Gradio Demo fo CLIP model. \n This demo is based on assessment for the 🤗 Huggingface course 2. \n To use it, simply write which image you are looking for. Read more at the links below.",
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  article = "You find more information about this demo on my ✨ github repository [marcelcastrobr](https://github.com/marcelcastrobr/huggingface_course2)",
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  fn=search_text,
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+ inputs=[gr.Textbox(lines=4,
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  label="Write what you are looking for in an image...",
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  placeholder="Text Here..."),
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+ gr.Slider(0, 5, step=1)],
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+ outputs=[gr.Gallery(
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+ label="Generated images", show_label=False, elem_id="gallery"
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+ ).style(grid=[2], height="auto")]
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  ,examples=[[("Dog in the beach"), 2],
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  [("Paris during night."), 1],
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  [("A cute kangaroo"), 5],
requirements.txt CHANGED
@@ -1,3 +1,4 @@
1
  transformers
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  sentence-transformers
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- torch
 
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  transformers
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  sentence-transformers
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+ torch
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+ gradio