Toy
Claude
commited on
Commit
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e8460b8
1
Parent(s):
5aeda0b
Fix Python 3.9 compatibility - replace union syntax | with Union
Browse files- Replace all `Type | None` syntax with `Union[Type, None]`
- Add typing.Union imports where needed
- Ensures compatibility with Python 3.9.13 on HuggingFace Spaces
π€ Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- .python-version +1 -1
- src/services/models/flower_classification.py +3 -3
- src/services/models/image_generation.py +3 -1
- src/services/training/dataset.py +2 -1
- src/ui/french_style/french_style_tab.py +3 -2
- src/ui/generate/generate_tab.py +2 -1
- src/ui/identify/identify_tab.py +3 -3
- src/utils/color_utils.py +2 -1
.python-version
CHANGED
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@@ -1 +1 @@
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-
3.
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+
3.12.11
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src/services/models/flower_classification.py
CHANGED
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@@ -3,7 +3,7 @@ Flower classification service using ConvNeXt and CLIP models.
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"""
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import os
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-
from typing import Any
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import torch
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from PIL import Image
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@@ -88,8 +88,8 @@ class FlowerClassificationService:
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def identify_flowers(
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self,
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image: Image.Image
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candidate_labels: list[str]
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top_k: int = 7,
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min_score: float = 0.12,
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) -> tuple[list[list[Any]], str]:
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"""
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import os
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+
from typing import Any, Union
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import torch
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from PIL import Image
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def identify_flowers(
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self,
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image: Union[Image.Image, None],
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candidate_labels: Union[list[str], None] = None,
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top_k: int = 7,
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min_score: float = 0.12,
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) -> tuple[list[list[Any]], str]:
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src/services/models/image_generation.py
CHANGED
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@@ -1,5 +1,7 @@
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"""Image generation service using SDXL models."""
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import numpy as np
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import torch
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from diffusers import AutoPipelineForText2Image
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@@ -89,7 +91,7 @@ class ImageGenerationService:
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steps: int = 4,
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width: int = 1024,
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height: int = 1024,
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-
seed: int
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) -> Image.Image:
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"""Generate an image from a text prompt."""
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if seed is None or seed < 0:
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"""Image generation service using SDXL models."""
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from typing import Union
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import numpy as np
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import torch
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from diffusers import AutoPipelineForText2Image
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steps: int = 4,
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width: int = 1024,
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height: int = 1024,
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seed: Union[int, None] = None,
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) -> Image.Image:
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"""Generate an image from a text prompt."""
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if seed is None or seed < 0:
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src/services/training/dataset.py
CHANGED
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@@ -3,6 +3,7 @@ Dataset class for flower training data.
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"""
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import os
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import torch
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from PIL import Image
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"""Dataset for flower classification training."""
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def __init__(
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self, image_dir: str, processor, flower_labels: list[str]
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):
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self.image_paths = []
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self.labels = []
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"""
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import os
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from typing import Union
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import torch
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from PIL import Image
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"""Dataset for flower classification training."""
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def __init__(
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self, image_dir: str, processor, flower_labels: Union[list[str], None] = None
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):
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self.image_paths = []
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self.labels = []
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src/ui/french_style/french_style_tab.py
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@@ -1,6 +1,7 @@
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"""
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French Style tab UI components and logic.
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"""
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import gradio as gr
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from PIL import Image
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return "π Processing... Please wait while we analyze your flower image...", ""
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def analyze_and_generate(
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self, image: Image.Image
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) -> tuple[Image.Image
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"""Analyze uploaded flower image and generate French-style arrangement."""
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if image is None:
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return None, "Please upload an image", ""
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"""
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French Style tab UI components and logic.
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"""
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from typing import Union
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import gradio as gr
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from PIL import Image
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return "π Processing... Please wait while we analyze your flower image...", ""
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def analyze_and_generate(
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self, image: Union[Image.Image, None]
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) -> tuple[Union[Image.Image, None], str, str]:
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"""Analyze uploaded flower image and generate French-style arrangement."""
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if image is None:
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return None, "Please upload an image", ""
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src/ui/generate/generate_tab.py
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@@ -1,6 +1,7 @@
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"""
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Generate tab UI components and logic.
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"""
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import gradio as gr
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from PIL import Image
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def generate_image(
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self, prompt: str, steps: int, width: int, height: int, seed: int
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-
) -> Image.Image
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"""Generate an image from the given parameters."""
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try:
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return image_generator.generate( # type: ignore
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"""
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Generate tab UI components and logic.
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"""
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from typing import Union
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import gradio as gr
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from PIL import Image
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def generate_image(
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self, prompt: str, steps: int, width: int, height: int, seed: int
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) -> Union[Image.Image, None]:
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"""Generate an image from the given parameters."""
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try:
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return image_generator.generate( # type: ignore
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src/ui/identify/identify_tab.py
CHANGED
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@@ -2,7 +2,7 @@
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Identify tab UI components and logic.
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"""
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-
from typing import Any
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import gradio as gr
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from PIL import Image
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def identify_flowers(
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self,
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image: Image.Image
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candidate_labels: list[str],
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top_k: int,
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min_score: float,
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min_score=min_score,
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)
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def set_image(self, image: Image.Image
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"""Set the image for identification (used by other tabs)."""
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return image
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Identify tab UI components and logic.
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"""
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from typing import Any, Union
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import gradio as gr
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from PIL import Image
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def identify_flowers(
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self,
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image: Union[Image.Image, None],
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candidate_labels: list[str],
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top_k: int,
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min_score: float,
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min_score=min_score,
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)
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def set_image(self, image: Union[Image.Image, None]) -> Union[Image.Image, None]:
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"""Set the image for identification (used by other tabs)."""
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return image
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src/utils/color_utils.py
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@@ -1,6 +1,7 @@
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"""
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Color analysis utilities.
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"""
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import numpy as np
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from PIL import Image
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def extract_dominant_colors(
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image: Image.Image
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) -> tuple[list[str], np.ndarray]:
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"""Extract dominant colors from an image using k-means clustering."""
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if image is None:
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"""
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Color analysis utilities.
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"""
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+
from typing import Union
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import numpy as np
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from PIL import Image
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def extract_dominant_colors(
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image: Union[Image.Image, None], num_colors: int = 5
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) -> tuple[list[str], np.ndarray]:
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"""Extract dominant colors from an image using k-means clustering."""
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if image is None:
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