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| from flask import Flask, request, jsonify, send_from_directory | |
| import tensorflow as tf | |
| import numpy as np | |
| import json | |
| from tensorflow.keras.preprocessing import image | |
| from PIL import Image | |
| import io | |
| import os | |
| import smtplib | |
| from email.mime.multipart import MIMEMultipart | |
| from email.mime.text import MIMEText | |
| from datetime import datetime | |
| from flask_cors import CORS | |
| app = Flask(__name__, static_folder='.', static_url_path='') | |
| CORS(app) | |
| # ───────────────────────────────────────────── | |
| # Paths (relative — works on HuggingFace) | |
| # ───────────────────────────────────────────── | |
| WEIGHTS_PATH = "best_weights.weights.h5" | |
| ARCH_PATH = "model_architecture.json" | |
| CLASS_NAMES_PATH = "class_names.json" | |
| SYMPTOMS_PATH = "symptoms.json" | |
| MEDICINES_PATH = "medicines.json" | |
| IMG_SIZE = (224, 224) | |
| PORT = 7860 | |
| # ───────────────────────────────────────────── | |
| # Email Configuration | |
| # ───────────────────────────────────────────── | |
| SENDER_EMAIL = "angrajkarn2004@gmail.com" | |
| SENDER_PASSWORD = "wpjh gfuv ipma ibyi" | |
| # ───────────────────────────────────────────── | |
| # Load Model & Data | |
| # ───────────────────────────────────────────── | |
| print("Loading model architecture from JSON...") | |
| with open(ARCH_PATH, 'r', encoding='utf-8') as f: | |
| model_json = f.read() | |
| model = tf.keras.models.model_from_json(model_json) | |
| print("Loading trained weights...") | |
| model.load_weights(WEIGHTS_PATH) | |
| with open(CLASS_NAMES_PATH, 'r', encoding='utf-8') as f: | |
| class_names = json.load(f) | |
| with open(SYMPTOMS_PATH, 'r', encoding='utf-8') as f: | |
| DISEASE_SYMPTOMS = json.load(f) | |
| with open(MEDICINES_PATH, 'r', encoding='utf-8') as f: | |
| MEDICINES_DB = json.load(f) | |
| print(f"Model and data loaded! {len(class_names)} classes ready.") | |
| # ───────────────────────────────────────────── | |
| # Image Preprocessing (identical to local backend) | |
| # ───────────────────────────────────────────── | |
| def preprocess_image(img_bytes): | |
| img = Image.open(io.BytesIO(img_bytes)).convert('RGB').resize(IMG_SIZE) | |
| img_array = image.img_to_array(img) | |
| img_array = np.expand_dims(img_array, axis=0) | |
| img_array = (img_array / 127.5) - 1.0 # ← exact same as local backend | |
| return img_array | |
| # ───────────────────────────────────────────── | |
| # Medicine Lookup | |
| # ───────────────────────────────────────────── | |
| def get_medicine_info(disease_name): | |
| return MEDICINES_DB.get(disease_name, {}) | |
| # ───────────────────────────────────────────── | |
| # Medicine HTML Block (for email) | |
| # ───────────────────────────────────────────── | |
| def build_medicine_html_block(meds): | |
| if not meds: | |
| return "<p style='color:#6b7280;'>No specific medication data available.</p>" | |
| SECTION_LABELS = { | |
| "topical": "Topical Treatment", "oral_moderate": "Oral Treatment (Moderate)", | |
| "oral_severe": "Oral Treatment (Severe)", "systemic": "Systemic Treatment", | |
| "first_line": "First-Line Treatment", "adjuvants": "Adjuvant Therapy", | |
| "antipruritic": "Antipruritic (Itch Relief)", "antihistamines": "Antihistamines", | |
| "emollients": "Emollients / Moisturizers", "surgical": "Surgical Treatment", | |
| "immunotherapy": "Immunotherapy", "targeted_therapy": "Targeted Therapy", | |
| "biologics_psoriasis": "Biologic Therapy", "systemic_psoriasis": "Systemic (Psoriasis)", | |
| "topical_psoriasis": "Topical (Psoriasis)", "lichen_planus": "Lichen Planus Treatment", | |
| "rosacea_specific": "Rosacea-Specific", "vitiligo": "Vitiligo Treatment", | |
| "melasma": "Melasma Treatment", "photodermatoses": "Photodermatosis Treatment", | |
| "actinic_keratosis": "Actinic Keratosis", "basal_cell_carcinoma": "Basal Cell Carcinoma", | |
| "squamous_cell_carcinoma": "Squamous Cell Carcinoma", | |
| "impetigo_topical": "Impetigo (Topical)", "cellulitis_oral": "Cellulitis (Oral)", | |
| "severe_iv": "Severe / IV Therapy", "scabies_first_line": "Scabies First-Line", | |
| "scabies_adjuncts": "Scabies Adjuncts", "lyme_disease": "Lyme Disease", | |
| "insect_bites": "Insect Bite Relief", "onychomycosis_topical": "Nail Fungus (Topical)", | |
| "onychomycosis_oral": "Nail Fungus (Oral)", "nail_psoriasis": "Nail Psoriasis", | |
| "tinea_topical": "Tinea (Topical)", "tinea_oral": "Tinea (Oral)", | |
| "candidiasis": "Candidiasis", "acute_urticaria": "Acute Urticaria", | |
| "chronic_urticaria": "Chronic Urticaria", "anaphylaxis_emergency": "Anaphylaxis Emergency", | |
| "herpes_simplex": "Herpes Simplex", "herpes_zoster": "Herpes Zoster", | |
| "hpv_warts": "HPV / Warts", "androgenetic_alopecia": "Androgenetic Alopecia", | |
| "alopecia_areata": "Alopecia Areata", "telogen_effluvium": "Telogen Effluvium", | |
| "tinea_capitis": "Tinea Capitis", "mild": "Mild Cases", | |
| "moderate_to_severe": "Moderate-Severe Cases", | |
| "allergic_contact_dermatitis": "Allergic Contact Dermatitis", | |
| "mild_to_moderate": "Mild to Moderate", "sjs_ten_emergency": "SJS / TEN Emergency", | |
| "infantile_hemangioma": "Infantile Hemangioma", "pyogenic_granuloma": "Pyogenic Granuloma", | |
| "port_wine_stain": "Port Wine Stain", "cherry_angioma": "Cherry Angioma", | |
| "cutaneous_small_vessel": "Cutaneous Vasculitis", "systemic_vasculitis": "Systemic Vasculitis", | |
| "cutaneous_lupus": "Cutaneous Lupus", "systemic_lupus": "Systemic Lupus (SLE)", | |
| "warts": "Warts Treatment", "molluscum_contagiosum": "Molluscum Contagiosum", | |
| "viral_skin_infections_general": "General Viral Care", | |
| "seborrheic_keratosis": "Seborrheic Keratosis", "dermatofibroma": "Dermatofibroma", | |
| "lipoma": "Lipoma", "general_approach": "General Approach", | |
| "diabetes_related": "Diabetes-Related Skin", "thyroid_related": "Thyroid-Related Skin", | |
| "liver_disease": "Liver Disease Skin", "bullous_pemphigoid": "Bullous Pemphigoid", | |
| "wound_care": "Wound / Erosion Care", "topical_steroids": "Topical Steroids", | |
| "calcineurin_inhibitors": "Calcineurin Inhibitors", "supportive": "Supportive Care", | |
| } | |
| SKIP_KEYS = {"monitoring", "caution"} | |
| html = "" | |
| for key, value in meds.items(): | |
| if key in SKIP_KEYS: | |
| continue | |
| label = SECTION_LABELS.get(key, key.replace("_", " ").title()) | |
| if isinstance(value, list): | |
| items = "".join(f"<li style='margin-bottom:4px;'>{item}</li>" for item in value) | |
| html += f""" | |
| <div style="margin-bottom:16px; padding:12px 16px; background:#f9fafb; | |
| border-radius:6px; border-left:3px solid #0d9488;"> | |
| <div style="font-size:12px; font-weight:700; color:#0d9488; | |
| text-transform:uppercase; letter-spacing:1px; | |
| margin-bottom:8px;">💊 {label}</div> | |
| <ul style="margin:0; padding-left:18px; color:#374151; | |
| font-size:14px; line-height:1.8;">{items}</ul> | |
| </div>""" | |
| elif isinstance(value, str): | |
| html += f""" | |
| <div style="margin-bottom:12px; padding:10px 16px; background:#f9fafb; | |
| border-radius:6px; border-left:3px solid #0d9488;"> | |
| <div style="font-size:12px; font-weight:700; color:#0d9488; | |
| text-transform:uppercase; letter-spacing:1px; | |
| margin-bottom:4px;">📌 {label}</div> | |
| <p style="margin:0; color:#374151; font-size:14px;">{value}</p> | |
| </div>""" | |
| if meds.get("monitoring"): | |
| html += f""" | |
| <div style="background:#f0f9ff; border-left:4px solid #0ea5e9; | |
| padding:12px 16px; border-radius:4px; margin-top:10px; font-size:13px; color:#0c4a6e;"> | |
| <strong>📊 Monitoring:</strong> {meds['monitoring']} | |
| </div>""" | |
| if meds.get("caution"): | |
| html += f""" | |
| <div style="background:#fff7ed; border-left:4px solid #f59e0b; | |
| padding:12px 16px; border-radius:4px; margin-top:10px; font-size:13px; color:#92400e;"> | |
| <strong>⚠️ Caution:</strong> {meds['caution']} | |
| </div>""" | |
| return html | |
| def build_medicine_plain_block(meds): | |
| if not meds: | |
| return " No specific medication data available.\n" | |
| SKIP_KEYS = {"monitoring", "caution"} | |
| text = "" | |
| for key, value in meds.items(): | |
| if key in SKIP_KEYS: | |
| continue | |
| label = key.replace("_", " ").upper() | |
| if isinstance(value, list): | |
| text += f"\n [{label}]\n" + "".join(f" - {item}\n" for item in value) | |
| elif isinstance(value, str): | |
| text += f"\n [{label}]\n {value}\n" | |
| if meds.get("monitoring"): | |
| text += f"\n [MONITORING]\n {meds['monitoring']}\n" | |
| if meds.get("caution"): | |
| text += f"\n [CAUTION]\n {meds['caution']}\n" | |
| return text | |
| # ───────────────────────────────────────────── | |
| # Email Builders | |
| # ───────────────────────────────────────────── | |
| def build_email_html(name, age, email, phone, symptoms_text, | |
| disease, confidence, match_score, matching, missing, meds): | |
| report_date = datetime.now().strftime("%B %d, %Y %H:%M") | |
| matching_str = ", ".join(matching) if matching else "None" | |
| missing_str = ", ".join(missing) if missing else "None" | |
| medicine_block = build_medicine_html_block(meds) | |
| return f"""<!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <style> | |
| body {{ font-family:'Segoe UI',Arial,sans-serif; background:#f4f4f4; margin:0; padding:0; }} | |
| .wrapper {{ max-width:700px; margin:30px auto; background:#fff; border-radius:10px; | |
| box-shadow:0 4px 18px rgba(0,0,0,0.10); overflow:hidden; }} | |
| .header {{ background:#0d9488; padding:28px 36px; color:#fff; }} | |
| .header h1 {{ font-size:24px; margin:0 0 4px; letter-spacing:1px; }} | |
| .header p {{ margin:0; font-size:13px; opacity:0.85; }} | |
| .info-bar {{ background:#f0fdfa; padding:16px 36px; border-bottom:1px solid #ccf0ec; | |
| display:flex; gap:40px; flex-wrap:wrap; }} | |
| .info-bar span {{ font-size:13px; color:#374151; }} | |
| .info-bar strong {{ color:#0d9488; }} | |
| .body {{ padding:28px 36px; }} | |
| .sec {{ font-size:13px; font-weight:700; text-transform:uppercase; | |
| letter-spacing:1.2px; color:#0d9488; margin:24px 0 12px; | |
| border-bottom:1px solid #e5f4f3; padding-bottom:4px; }} | |
| table {{ width:100%; border-collapse:collapse; font-size:15px; }} | |
| td {{ padding:9px 6px; vertical-align:top; }} | |
| td.lbl {{ width:45%; color:#6b7280; font-weight:500; }} | |
| td.val {{ color:#111827; font-weight:600; }} | |
| tr:nth-child(even) td {{ background:#f9fafb; }} | |
| .disclaimer {{ background:#fff7ed; border-left:4px solid #f59e0b; padding:12px 16px; | |
| border-radius:4px; font-size:13px; color:#92400e; margin-top:20px; }} | |
| .footer {{ background:#f0fdfa; padding:18px 36px; font-size:12px; color:#6b7280; | |
| border-top:1px solid #ccf0ec; text-align:center; }} | |
| .footer strong {{ color:#0d9488; }} | |
| </style> | |
| </head> | |
| <body> | |
| <div class="wrapper"> | |
| <div class="header"> | |
| <h1>🩺 DermAI — Skin Condition Report</h1> | |
| <p>Generated on {report_date}</p> | |
| </div> | |
| <div class="info-bar"> | |
| <span><strong>Patient:</strong> {name}</span> | |
| <span><strong>Age:</strong> {age}</span> | |
| <span><strong>Email:</strong> {email}</span> | |
| {"<span><strong>Phone:</strong> " + phone + "</span>" if phone else ""} | |
| </div> | |
| <div class="body"> | |
| <p style="font-size:15px; color:#374151; margin-top:0;"> | |
| Dear <strong>{name}</strong>,<br><br> | |
| Thank you for using <strong>DermAI Skin Condition Analyzer</strong>. | |
| Below is your personalized analysis report based on the image and symptoms provided. | |
| </p> | |
| <div class="sec">📋 Analysis Summary</div> | |
| <table> | |
| <tr><td class="lbl">Predicted Condition</td><td class="val">{disease}</td></tr> | |
| <tr><td class="lbl">Confidence Level</td><td class="val">{confidence}%</td></tr> | |
| <tr><td class="lbl">Symptom Alignment</td><td class="val">{match_score}</td></tr> | |
| <tr><td class="lbl">Symptoms You Reported</td><td class="val">{symptoms_text or "None"}</td></tr> | |
| <tr><td class="lbl">Matching Symptoms</td><td class="val">{matching_str}</td></tr> | |
| <tr><td class="lbl">Additional Notes</td><td class="val" style="color:#6b7280;font-weight:400;">{missing_str}</td></tr> | |
| </table> | |
| <div class="sec">💊 Recommended Medications & Treatment Protocol</div> | |
| <p style="font-size:13px;color:#6b7280;margin-top:-8px;margin-bottom:14px;"> | |
| Based on standard clinical guidelines for the predicted condition. | |
| These are <em>reference guidelines only</em> — always follow your dermatologist's prescription. | |
| </p> | |
| {medicine_block} | |
| <div class="sec">🛡️ General Skin Care Tips</div> | |
| <ul style="padding-left:20px; color:#374151; font-size:14px; line-height:2.0;"> | |
| <li>Keep the affected area clean and dry at all times.</li> | |
| <li>Avoid scratching, rubbing, or picking at the skin.</li> | |
| <li>Use gentle, fragrance-free moisturizers if dryness is present.</li> | |
| <li>Apply broad-spectrum SPF 30+ sunscreen every morning.</li> | |
| <li>Consult a licensed dermatologist for a confirmed diagnosis and personalized treatment.</li> | |
| </ul> | |
| <div class="disclaimer"> | |
| ⚠️ <strong>Disclaimer:</strong> This report is for <em>informational purposes only</em>. | |
| Do <strong>NOT</strong> self-medicate. Always consult a qualified healthcare professional. | |
| </div> | |
| </div> | |
| <div class="footer"> | |
| <strong>DermAI</strong> — Skin Condition Analyzer | For educational use only<br> | |
| This is an automated report. Please do not reply to this email. | |
| </div> | |
| </div> | |
| </body> | |
| </html>""" | |
| def build_email_plain(name, age, symptoms_text, | |
| disease, confidence, match_score, matching, missing, meds): | |
| report_date = datetime.now().strftime("%B %d, %Y %H:%M") | |
| matching_str = ", ".join(matching) if matching else "None" | |
| missing_str = ", ".join(missing) if missing else "None" | |
| medicine_text = build_medicine_plain_block(meds) | |
| return f""" | |
| ============================================================ | |
| DermAI — Skin Condition Report | |
| Generated: {report_date} | |
| ============================================================ | |
| Dear {name}, | |
| PATIENT DETAILS | |
| Name : {name} | |
| Age : {age} | |
| ANALYSIS SUMMARY | |
| Predicted Condition : {disease} | |
| Confidence Level : {confidence}% | |
| Symptom Alignment : {match_score} | |
| Symptoms You Reported : {symptoms_text or "None"} | |
| Matching Symptoms : {matching_str} | |
| Additional Notes : {missing_str} | |
| RECOMMENDED MEDICATIONS & TREATMENT PROTOCOL | |
| {medicine_text} | |
| GENERAL SKIN CARE TIPS | |
| - Keep the affected area clean and dry. | |
| - Avoid scratching or rubbing the skin. | |
| - Use gentle, fragrance-free moisturizers if dryness is present. | |
| - Apply SPF 30+ sunscreen daily. | |
| - Consult a licensed dermatologist for a confirmed diagnosis. | |
| ------------------------------------------------------------ | |
| DISCLAIMER: This report is for informational purposes only | |
| and does NOT constitute a personal prescription. | |
| Do NOT self-medicate. Consult a qualified healthcare professional. | |
| ------------------------------------------------------------ | |
| DermAI — Skin Condition Analyzer | For educational use only | |
| """ | |
| # ───────────────────────────────────────────── | |
| # Send Email | |
| # ───────────────────────────────────────────── | |
| def send_report_email(recipient_email, recipient_name, age, phone, symptoms_text, | |
| disease, confidence, match_score, matching, missing, meds): | |
| try: | |
| msg = MIMEMultipart("alternative") | |
| msg["Subject"] = f"DermAI Report — {disease}" | |
| msg["From"] = f"DermAI <{SENDER_EMAIL}>" | |
| msg["To"] = recipient_email | |
| plain = build_email_plain(recipient_name, age, symptoms_text, | |
| disease, confidence, match_score, matching, missing, meds) | |
| html = build_email_html(recipient_name, age, recipient_email, phone, symptoms_text, | |
| disease, confidence, match_score, matching, missing, meds) | |
| msg.attach(MIMEText(plain, "plain")) | |
| msg.attach(MIMEText(html, "html")) | |
| with smtplib.SMTP_SSL("smtp.gmail.com", 465) as server: | |
| server.login(SENDER_EMAIL, SENDER_PASSWORD) | |
| server.sendmail(SENDER_EMAIL, recipient_email, msg.as_string()) | |
| print(f"Email sent to {recipient_email}") | |
| return True | |
| except Exception as e: | |
| print(f"Email failed: {e}") | |
| return False | |
| # ───────────────────────────────────────────── | |
| # Routes | |
| # ───────────────────────────────────────────── | |
| def serve_index(): | |
| return send_from_directory('.', 'index.html') | |
| def predict(): | |
| try: | |
| if 'file' not in request.files: | |
| return jsonify({"error": "No file uploaded"}), 400 | |
| file = request.files['file'] | |
| if file.filename == '': | |
| return jsonify({"error": "No file selected"}), 400 | |
| user_info = {} | |
| if 'user_info' in request.form: | |
| try: | |
| user_info = json.loads(request.form['user_info']) | |
| except Exception: | |
| pass | |
| user_name = user_info.get("name", "Patient") | |
| user_age = user_info.get("age", "N/A") | |
| user_email = user_info.get("email", "") | |
| user_phone = user_info.get("phone", "") | |
| symptoms_text = user_info.get("symptoms", "") | |
| user_symptoms = [s.strip() for s in symptoms_text.replace(",", " ").split() if s.strip()] | |
| # Predict | |
| img_bytes = file.read() | |
| processed_img = preprocess_image(img_bytes) | |
| predictions = model.predict(processed_img)[0] | |
| top_idx = int(np.argmax(predictions)) | |
| confidence = float(predictions[top_idx] * 100) | |
| predicted_disease = class_names[top_idx] # ← loaded from class_names.json | |
| # Symptom matching | |
| known_symptoms = DISEASE_SYMPTOMS.get(predicted_disease, []) | |
| matching = [s for s in user_symptoms if any(s.lower() == k.lower() for k in known_symptoms)] | |
| missing = [k for k in known_symptoms if not any(k.lower() == u.lower() for u in user_symptoms)] | |
| match_score = ( | |
| f"{len(matching)} of {len(known_symptoms)} typical symptoms match" | |
| if known_symptoms else "No symptom data available" | |
| ) | |
| confidence_str = f"{confidence:.2f}" | |
| meds = get_medicine_info(predicted_disease) | |
| email_sent = False | |
| if user_email: | |
| email_sent = send_report_email( | |
| recipient_email = user_email, | |
| recipient_name = user_name, | |
| age = user_age, | |
| phone = user_phone, | |
| symptoms_text = symptoms_text, | |
| disease = predicted_disease, | |
| confidence = confidence_str, | |
| match_score = match_score, | |
| matching = matching, | |
| missing = missing, | |
| meds = meds | |
| ) | |
| return jsonify({ | |
| "disease": predicted_disease, | |
| "confidence": confidence_str, | |
| "match_score": match_score, | |
| "matching": matching, | |
| "missing": missing, | |
| "medicines": meds, | |
| "email_sent": email_sent | |
| }) | |
| except Exception as e: | |
| print("Error:", e) | |
| return jsonify({"error": "Prediction failed"}), 500 | |
| # ───────────────────────────────────────────── | |
| # Entry Point | |
| # ───────────────────────────────────────────── | |
| if __name__ == '__main__': | |
| print(f"\nDermAI server starting on port {PORT}\n") | |
| app.run(host='0.0.0.0', port=PORT, debug=False) |