AI-LAB-4

Sleeping

App Files Files Community

Rammohan0504 commited on Jun 27

Commit

7149a12

verified ·

1 Parent(s): ff02b4a

Update app.py

Browse files

Files changed (1) hide show

app.py +41 -30

app.py CHANGED Viewed

@@ -16,9 +16,15 @@ import glob
 # Cleanup temporary files on exit
 def cleanup_temp_files():
     for temp_file in glob.glob("/tmp/Health_Report_*.pdf"):
-        os.remove(temp_file)
-    for temp_file in glob.glob("/tmp/health_card.html"):
-        os.remove(temp_file)
 atexit.register(cleanup_temp_files)
 # Initialize the face mesh model
@@ -130,7 +136,7 @@ def build_table(title, rows):
 def save_results_to_pdf(profile_image_base64, test_results, summary, patient_name, patient_age, patient_gender, patient_id, filename):
     try:
         # Generate HTML content
-        current_date = datetime.now().strftime("%B %d, %Y")
         health_card_html = f"""
         <!DOCTYPE html>
         <html>
@@ -195,36 +201,41 @@ def save_results_to_pdf(profile_image_base64, test_results, summary, patient_nam
         # Save HTML to a temporary file
         html_temp_path = "/tmp/health_card.html"
-        os.makedirs(os.path.dirname(html_temp_path), exist_ok=True)
-        with open(html_temp_path, "w", encoding="utf-8") as f:
-            f.write(health_card_html)
-        print(f"HTML saved to: {html_temp_path}")
         # Convert HTML to PDF using pdfkit
-        pdfkit.from_file(html_temp_path, filename, options={"quiet": ""})
-        print(f"PDF generated successfully at: {filename}")  # Debug log
         # Move to /tmp for Gradio access
         temp_pdf_path = "/tmp/" + os.path.basename(filename)
-        shutil.copy(filename, temp_pdf_path)
-        if os.path.exists(temp_pdf_path) and os.access(temp_pdf_path, os.R_OK):
-            return f"PDF saved successfully as {filename}", temp_pdf_path
-        else:
-            return "Error: PDF file not accessible.", None
     except Exception as e:
-        print(f"Error saving PDF: {str(e)}")  # Debug log
-        # Fallback: Save HTML for manual conversion
-        html_fallback_path = "/tmp/health_card_fallback.html"
-        with open(html_fallback_path, "w", encoding="utf-8") as f:
-            f.write(health_card_html)
-        print(f"Fallback HTML saved to: {html_fallback_path}")
-        return f"Error saving PDF: {str(e)}. Fallback HTML saved at {html_fallback_path}", None
 # Build health card layout
 def build_health_card(profile_image, test_results, summary, pdf_filepath, patient_name="", patient_age="", patient_gender="", patient_id=""):
-    from datetime import datetime
-    current_date = datetime.now().strftime("%B %d, %Y")
     pdf_filename = os.path.basename(pdf_filepath) if pdf_filepath else "health_report.pdf"
@@ -291,7 +302,7 @@ current_patient_details = {'name': '', 'age': '', 'gender': '', 'id': ''}
 # Modified analyze_face function
 def analyze_face(input_data):
-    if isinstance(input_data, str):  # Video input (file path in Replit)
         cap = cv2.VideoCapture(input_data)
         if not cap.isOpened():
             return "<div style='color:red;'>⚠️ Error: Could not open video.</div>", None
@@ -416,7 +427,7 @@ def route_inputs(mode, image, video, patient_name, patient_age, patient_gender,
 # Create Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("""# 🧠 Face-Based Lab Test AI Report (Video Mode)""")
     with gr.Row():
         with gr.Column():
             gr.Markdown("### Patient Information")
@@ -434,12 +445,12 @@ with gr.Blocks() as demo:
                                    sources=["upload", "webcam"])
             submit_btn = gr.Button("🔍 Analyze")
         with gr.Column():
-            result_html = gr.HTML(label="🧪 Health Report Table")
             result_pdf = gr.File(label="Download Health Report PDF", interactive=False)
             submit_btn.click(fn=route_inputs,
                              inputs=[mode_selector, image_input, video_input, patient_name, patient_age, patient_gender, patient_id],
                              outputs=[result_html, result_pdf])
-# Launch Gradio for Replit
-demo.launch(server_name="0.0.0.0", server_port=7860)

 # Cleanup temporary files on exit
 def cleanup_temp_files():
     for temp_file in glob.glob("/tmp/Health_Report_*.pdf"):
+        try:
+            os.remove(temp_file)
+        except Exception as e:
+            print(f"Failed to clean up {temp_file}: {e}")
+    for temp_file in glob.glob("/tmp/health_card*.html"):
+        try:
+            os.remove(temp_file)
+        except Exception as e:
+            print(f"Failed to clean up {temp_file}: {e}")
 atexit.register(cleanup_temp_files)
 # Initialize the face mesh model
 def save_results_to_pdf(profile_image_base64, test_results, summary, patient_name, patient_age, patient_gender, patient_id, filename):
     try:
         # Generate HTML content
+        current_date = datetime.now().strftime("%B %d, %Y %I:%M %p IST")  # Adjusted for IST
         health_card_html = f"""
         <!DOCTYPE html>
         <html>
         # Save HTML to a temporary file
         html_temp_path = "/tmp/health_card.html"
+        try:
+            os.makedirs(os.path.dirname(html_temp_path), exist_ok=True)
+            with open(html_temp_path, "w", encoding="utf-8") as f:
+                f.write(health_card_html)
+            print(f"HTML saved to: {html_temp_path}")
+        except Exception as e:
+            print(f"Error saving HTML: {e}")
+            return f"Error: Failed to save HTML - {str(e)}", None
         # Convert HTML to PDF using pdfkit
+        try:
+            pdfkit.from_file(html_temp_path, filename, options={"quiet": ""})
+            print(f"PDF generated successfully at: {filename}")  # Debug log
+        except Exception as e:
+            print(f"Error converting to PDF: {str(e)}")
+            return f"Error: Failed to generate PDF - {str(e)}", None
         # Move to /tmp for Gradio access
         temp_pdf_path = "/tmp/" + os.path.basename(filename)
+        try:
+            shutil.copy(filename, temp_pdf_path)
+            if os.path.exists(temp_pdf_path) and os.access(temp_pdf_path, os.R_OK):
+                return f"PDF saved successfully as {filename}", temp_pdf_path
+            else:
+                return "Error: PDF file not accessible.", None
+        except Exception as e:
+            print(f"Error moving PDF: {e}")
+            return f"Error: Failed to move PDF - {str(e)}", None
     except Exception as e:
+        print(f"Unexpected error in save_results_to_pdf: {str(e)}")
+        return f"Error: Unexpected failure - {str(e)}", None
 # Build health card layout
 def build_health_card(profile_image, test_results, summary, pdf_filepath, patient_name="", patient_age="", patient_gender="", patient_id=""):
+    current_date = datetime.now().strftime("%B %d, %Y %I:%M %p IST")  # Adjusted for IST
     pdf_filename = os.path.basename(pdf_filepath) if pdf_filepath else "health_report.pdf"
 # Modified analyze_face function
 def analyze_face(input_data):
+    if isinstance(input_data, str):  # Video input (file path in Spaces)
         cap = cv2.VideoCapture(input_data)
         if not cap.isOpened():
             return "<div style='color:red;'>⚠️ Error: Could not open video.</div>", None
 # Create Gradio interface
 with gr.Blocks() as demo:
+    gr.Markdown("""# 🧠 Face-Based Lab Test AI Report""")
     with gr.Row():
         with gr.Column():
             gr.Markdown("### Patient Information")
                                    sources=["upload", "webcam"])
             submit_btn = gr.Button("🔍 Analyze")
         with gr.Column():
+            result_html = gr.HTML(label="🧪 Health Report")
             result_pdf = gr.File(label="Download Health Report PDF", interactive=False)
             submit_btn.click(fn=route_inputs,
                              inputs=[mode_selector, image_input, video_input, patient_name, patient_age, patient_gender, patient_id],
                              outputs=[result_html, result_pdf])
+# Launch Gradio for Hugging Face Spaces
+demo.launch()