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Runtime error
Daniel Verdu
commited on
Commit
•
4403f05
1
Parent(s):
6f8465a
first commit in hf_spaces
Browse files- deoldify/visualize.py +10 -11
deoldify/visualize.py
CHANGED
@@ -8,6 +8,7 @@ from PIL import Image
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from matplotlib.axes import Axes
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from matplotlib.figure import Figure
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from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
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import torch
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from fastai.core import *
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@@ -18,6 +19,7 @@ from .generators import gen_inference_deep, gen_inference_wide
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class ModelImageVisualizer:
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def __init__(self, filter: IFilter, results_dir: str = None):
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self.filter = filter
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@@ -29,11 +31,11 @@ class ModelImageVisualizer:
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# gc.collect()
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def _open_pil_image(self, path: Path) -> Image:
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return
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def _get_image_from_url(self, url: str) -> Image:
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response = requests.get(url, timeout=30, headers={'Accept': '*/*;q=0.8'})
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img =
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return img
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def plot_transformed_image_from_url(
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@@ -41,7 +43,7 @@ class ModelImageVisualizer:
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url: str,
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path: str = 'test_images/image.png',
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results_dir:Path = None,
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figsize:
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render_factor: int = None,
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display_render_factor: bool = False,
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@@ -66,7 +68,7 @@ class ModelImageVisualizer:
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self,
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path: str,
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results_dir:Path = None,
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figsize:
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render_factor: int = None,
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display_render_factor: bool = False,
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compare: bool = False,
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@@ -95,7 +97,7 @@ class ModelImageVisualizer:
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def plot_transformed_pil_image(
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self,
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input_image: Image,
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figsize:
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render_factor: int = None,
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display_render_factor: bool = False,
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compare: bool = False,
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@@ -117,7 +119,7 @@ class ModelImageVisualizer:
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def _plot_comparison(
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self,
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figsize:
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render_factor: int,
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display_render_factor: bool,
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orig: Image,
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@@ -141,7 +143,7 @@ class ModelImageVisualizer:
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def _plot_solo(
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self,
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figsize:
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render_factor: int,
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display_render_factor: bool,
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result: Image,
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@@ -172,9 +174,6 @@ class ModelImageVisualizer:
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orig_image, orig_image, render_factor=render_factor,post_process=post_process
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)
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# if watermarked:
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# return get_watermarked(filtered_image)
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return filtered_image
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def get_transformed_pil_image(
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@@ -208,7 +207,7 @@ class ModelImageVisualizer:
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backgroundcolor='black',
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)
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def _get_num_rows_columns(self, num_images: int, max_columns: int) ->
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columns = min(num_images, max_columns)
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rows = num_images // columns
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rows = rows if rows * columns == num_images else rows + 1
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from matplotlib.axes import Axes
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from matplotlib.figure import Figure
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from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
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from typing import Tuple
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import torch
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from fastai.core import *
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# class LoadedModel
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class ModelImageVisualizer:
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def __init__(self, filter: IFilter, results_dir: str = None):
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self.filter = filter
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# gc.collect()
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def _open_pil_image(self, path: Path) -> Image:
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return Image.open(path).convert('RGB')
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def _get_image_from_url(self, url: str) -> Image:
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response = requests.get(url, timeout=30, headers={'Accept': '*/*;q=0.8'})
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img = Image.open(BytesIO(response.content)).convert('RGB')
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return img
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def plot_transformed_image_from_url(
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url: str,
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path: str = 'test_images/image.png',
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results_dir:Path = None,
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figsize: Tuple[int, int] = (20, 20),
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render_factor: int = None,
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display_render_factor: bool = False,
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self,
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path: str,
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results_dir:Path = None,
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figsize: Tuple[int, int] = (20, 20),
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render_factor: int = None,
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display_render_factor: bool = False,
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compare: bool = False,
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def plot_transformed_pil_image(
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self,
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input_image: Image,
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figsize: Tuple[int, int] = (20, 20),
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render_factor: int = None,
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display_render_factor: bool = False,
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compare: bool = False,
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def _plot_comparison(
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self,
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figsize: Tuple[int, int],
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render_factor: int,
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display_render_factor: bool,
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orig: Image,
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def _plot_solo(
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self,
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figsize: Tuple[int, int],
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render_factor: int,
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display_render_factor: bool,
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result: Image,
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orig_image, orig_image, render_factor=render_factor,post_process=post_process
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)
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return filtered_image
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def get_transformed_pil_image(
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backgroundcolor='black',
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)
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def _get_num_rows_columns(self, num_images: int, max_columns: int) -> Tuple[int, int]:
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columns = min(num_images, max_columns)
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rows = num_images // columns
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rows = rows if rows * columns == num_images else rows + 1
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