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README.md
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README.md
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@ -29,53 +29,46 @@ Load the model parameters once and reuse the model to generate multiple images.
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```python
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```python
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from min_dalle import MinDalle
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from min_dalle import MinDalle
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model = MinDalle(is_mega=True, models_root='./pretrained')
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model = MinDalle(
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is_mega=True,
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is_reusable=True,
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models_root='./pretrained'
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)
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```
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```
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The required models will be downloaded to `models_root` if they are not already there. Once everything has finished initializing, call `generate_image` with some text as many times as you want.
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The required models will be downloaded to `models_root` if they are not already there. Once everything has finished initializing, call `generate_image` with some text as many times as you want.
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```python
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```python
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text = 'Dali painting of WALL·E'
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image = model.generate_image(
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image = model.generate_image(text, grid_size=4)
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'Dali painting of WALL·E',
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seed=-1,
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grid_size=4,
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log2_supercondition_factor=3
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)
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display(image)
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display(image)
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```
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```
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/dali_walle.jpg" alt="min-dalle" width="300"/>
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/dali_walle.jpg" alt="min-dalle" width="300"/>
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```python
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Use a positive `seed` for reproducible results. Higher values for `log2_supercondition_factor` result in better agreement with the text but a narrower variety of generated images.
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text = 'Rusty Iron Man suit found abandoned in the woods being reclaimed by nature'
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image = model.generate_image(text, grid_size=3)
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If the model is being used interactively (e.g. in a notebook) `generate_image_stream` can be used to generate a stream of images as it the model is decoding. The detokenizer adds a slight delay for each intermediate image.
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display(image)
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```
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/ironman.jpg" alt="min-dalle" width="300"/>
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```python
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```python
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text = 'court sketch of godzilla on trial'
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image_stream = model.generate_image_stream(
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image = model.generate_image(text, grid_size=3)
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text='Dali painting of WALL·E',
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display(image)
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seed=-1,
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```
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grid_size=3,
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/godzilla_trial.jpg" alt="min-dalle" width="300"/>
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log2_mid_count=3,
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log2_supercondition_factor=3
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)
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```python
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is_first = True
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text = 'a funeral at Whole Foods'
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for image in image_stream:
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image = model.generate_image(text, grid_size=3)
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display_image = display if is_first else update_display
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display(image)
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display_image(image, display_id=1)
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is_first = False
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```
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```
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/funeral.jpg" alt="min-dalle" width="300"/>
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/dali_walle_animated.gif" alt="min-dalle" width="300"/>
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```python
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text = 'Jesus turning water into wine on Americas Got Talent'
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image = model.generate_image(text, grid_size=3)
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display(image)
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```
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/jesus.jpg" alt="min-dalle" width="300"/>
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```python
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text = 'cctv footage of Yoda robbing a liquor store'
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image = model.generate_image(text, grid_size=3)
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display(image)
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```
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/yoda.jpg" alt="min-dalle" width="300"/>
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### Command Line
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### Command Line
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@ -85,8 +78,3 @@ Use `image_from_text.py` to generate images from the command line.
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$ python image_from_text.py --text='artificial intelligence' --no-mega
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$ python image_from_text.py --text='artificial intelligence' --no-mega
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```
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```
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/artificial_intelligence.jpg" alt="min-dalle" width="200"/>
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/artificial_intelligence.jpg" alt="min-dalle" width="200"/>
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```bash
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$ python image_from_text.py --text='trail cam footage of gollum eating watermelon' --mega --grid-size=3
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```
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<img src="https://github.com/kuprel/min-dalle/raw/main/examples/gollum_trailcam.jpg" alt="min-dalle" width="300"/>
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