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Build error
metadata v9
Browse files
app.py
CHANGED
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@@ -51,36 +51,10 @@ def build_database():
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for j, item in enumerate(batch):
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try:
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# Handle different image data formats
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if hasattr(img_data, 'numpy'):
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# If it's a tensor/array, convert to PIL
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img = Image.fromarray(img_data.numpy())
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elif isinstance(img_data, dict):
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# If it's a dictionary, try to get the image data
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if "bytes" in img_data:
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img = Image.open(BytesIO(img_data["bytes"]))
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elif "path" in img_data:
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img = Image.open(img_data["path"])
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else:
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print(f"❌ Formato de diccionario no soportado: {img_data.keys()}")
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continue
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elif isinstance(img_data, str):
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if img_data.startswith("http"):
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response = requests.get(img_data, timeout=10)
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response.raise_for_status()
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img = Image.open(BytesIO(response.content))
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else:
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img = Image.open(img_data)
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elif isinstance(img_data, Image.Image):
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img = img_data
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else:
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print(f"❌ Formato desconocido en imagen {i+j}: {type(img_data)}")
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continue
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img = img.convert("RGB")
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img_processed = preprocess_image(img)
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embedding = DeepFace.represent(
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@@ -95,9 +69,6 @@ def build_database():
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del img_processed
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gc.collect()
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except (requests.RequestException, UnidentifiedImageError) as e:
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print(f"❌ Falló descarga/lectura de imagen {i+j}: {e}")
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continue
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except Exception as e:
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print(f"❌ No se pudo procesar imagen {i+j}: {str(e)}")
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print(f"Error details: {type(e).__name__}")
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for j, item in enumerate(batch):
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try:
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# The image is already a PIL Image object
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img = item["image"]
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# Ensure image is in RGB mode
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img = img.convert("RGB")
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img_processed = preprocess_image(img)
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embedding = DeepFace.represent(
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del img_processed
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gc.collect()
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except Exception as e:
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print(f"❌ No se pudo procesar imagen {i+j}: {str(e)}")
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print(f"Error details: {type(e).__name__}")
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