Update app.py
Browse files
app.py
CHANGED
@@ -60,13 +60,20 @@ islamic_advice = {
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}
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def analyze_combined(text, threshold, image):
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inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
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with torch.no_grad():
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logits_text = model(**inputs).logits
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probs_text = sigmoid(logits_text)[0]
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text_idx = torch.argmax(probs_text).item()
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text_label = model.config.id2label[text_idx].lower()
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if image:
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inputs_image = image_processor(images=image, return_tensors="pt")
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with torch.no_grad():
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@@ -74,14 +81,16 @@ def analyze_combined(text, threshold, image):
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probs_img = torch.nn.functional.softmax(logits_img, dim=1)[0]
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img_idx = torch.argmax(probs_img).item()
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img_label = image_model.config.id2label[img_idx].lower()
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custom_css = """
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@keyframes slideInUp {
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}
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def analyze_combined(text, threshold, image):
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# Text analysis
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inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
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with torch.no_grad():
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logits_text = model(**inputs).logits
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probs_text = sigmoid(logits_text)[0]
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text_idx = torch.argmax(probs_text).item()
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text_label = model.config.id2label[text_idx].lower()
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text_card = islamic_advice.get(text_label)
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if not text_card:
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text_card = get_gemini_advice_from_text(text)
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# Image analysis
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image_card = ""
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if image:
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inputs_image = image_processor(images=image, return_tensors="pt")
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with torch.no_grad():
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probs_img = torch.nn.functional.softmax(logits_img, dim=1)[0]
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img_idx = torch.argmax(probs_img).item()
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img_label = image_model.config.id2label[img_idx].lower()
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image_card = islamic_advice.get(img_label, f"<div class='notion-card fade-in'><h3>{img_label.capitalize()}</h3><p>May Allah guide your expression.</p></div>")
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return f"""
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<div class='notion-card fade-in slide-up glow-card'>
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<h2 style='text-align:center'>📝 From Text Analysis</h2>
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{text_card}
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</div>
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{f"<div class='notion-card fade-in slide-up glow-card'><h2 style='text-align:center'>🖼️ From Image Analysis</h2>{image_card}</div>" if image else ""}
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"""
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custom_css = """
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@keyframes slideInUp {
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