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e0bdd7f
1
Parent(s):
aa3f38a
Update app.py
Browse files
app.py
CHANGED
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@@ -5,12 +5,8 @@ from PIL import Image
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from datasets import load_dataset
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import random
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from datasets import load_from_disk
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dataset = load_from_disk("./train")
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from collections import OrderedDict
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FRUITS30_CLASSES = OrderedDict(
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{
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"0" : "acerolas",
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@@ -45,9 +41,7 @@ FRUITS30_CLASSES = OrderedDict(
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"29" : "watermelons"
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}
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)
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labels = list(FRUITS30_CLASSES.values())
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model, _, preprocess = open_clip.create_model_and_transforms('ViT-B-32', pretrained='laion2b_s34b_b79k')
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model.eval() # model in train mode by default, impacts some models with BatchNorm or stochastic depth active
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tokenizer = open_clip.get_tokenizer('ViT-B-32')
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@@ -55,7 +49,6 @@ tokenizer = open_clip.get_tokenizer('ViT-B-32')
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def create_interface():
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# Store current correct labels in a mutable container
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current_correct_labels = []
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def get_image():
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indices = random.sample(range(len(dataset)), 1)
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selected_images = [dataset[i]['image'] for i in indices]
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@@ -78,7 +71,7 @@ def create_interface():
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with gr.Blocks() as demo:
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# Create components
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with gr.Row():
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img1 = gr.Image(type="pil", label="Fruit")
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with gr.Row():
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label1 = gr.Textbox(label="Name this fruit")
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@@ -92,8 +85,6 @@ def create_interface():
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fn=get_image,
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outputs=[img1]
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)
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# Evaluate user input on submit button click
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submit_btn.click(
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fn=on_submit,
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@@ -101,7 +92,7 @@ def create_interface():
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outputs=result
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)
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demo.launch()
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# Run the game
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create_interface()
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from datasets import load_dataset
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import random
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from datasets import load_from_disk
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dataset = load_from_disk("./fruits_dataset/train/train")
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from collections import OrderedDict
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FRUITS30_CLASSES = OrderedDict(
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{
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"0" : "acerolas",
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"29" : "watermelons"
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}
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)
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labels = list(FRUITS30_CLASSES.values())
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model, _, preprocess = open_clip.create_model_and_transforms('ViT-B-32', pretrained='laion2b_s34b_b79k')
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model.eval() # model in train mode by default, impacts some models with BatchNorm or stochastic depth active
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tokenizer = open_clip.get_tokenizer('ViT-B-32')
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def create_interface():
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# Store current correct labels in a mutable container
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current_correct_labels = []
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def get_image():
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indices = random.sample(range(len(dataset)), 1)
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selected_images = [dataset[i]['image'] for i in indices]
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with gr.Blocks() as demo:
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# Create components
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with gr.Row():
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img1 = gr.Image(type="pil", label="Fruit",height = 256,width = 256)
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with gr.Row():
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label1 = gr.Textbox(label="Name this fruit")
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fn=get_image,
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outputs=[img1]
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)
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# Evaluate user input on submit button click
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submit_btn.click(
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fn=on_submit,
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outputs=result
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)
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demo.launch(debug = True)
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# Run the game
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create_interface()
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