Create app.py

app.py

@@ -0,0 +1,227 @@
+import gradio as gr
+import cv2
+import tempfile
+import os
+import requests
+import base64
+import random
+import string
+import json
+import ast
+
+    
+def check_nsfw(img_url):
+    session_hash = ''.join(random.choice(string.ascii_lowercase + string.digits) for _ in range(7))
+    data = {
+        'data': [
+            {'path': img_url},
+            "chen-convnext",
+            0.5,
+            True,
+            True
+            ],
+        'session_hash': session_hash,
+        'fn_index': 0,
+        'trigger_id': 12
+        }
+    r = requests.post('https://yoinked-da-nsfw-checker.hf.space/queue/join', json=data)
+
+    r = requests.get(f'https://yoinked-da-nsfw-checker.hf.space/queue/data?session_hash={session_hash}', stream=True)
+    buffer = ""  # Buffer to accumulate the chunks
+
+
+    for content in r.iter_content(100):
+        # Decode the byte content to a string
+        buffer += content.decode('utf-8')
+
+    return json.loads(buffer.split('data:')[len(buffer.split('data:'))-2])["output"]["data"][0]['label']
+    
+
+def check_nsfw2(img_url):
+    session_hash = ''.join(random.choice(string.ascii_lowercase + string.digits) for _ in range(7))
+    data = {
+        'data': [
+            {'path': img_url}
+            ],
+        'session_hash': session_hash,
+        'fn_index': 0,
+        'trigger_id': 9
+        }
+    r = requests.post('https://jamescookjr90-falconsai-nsfw-image-detection.hf.space/queue/join', json=data)
+
+    r = requests.get(f'https://jamescookjr90-falconsai-nsfw-image-detection.hf.space/queue/data?session_hash={session_hash}', stream=True)
+    buffer = ""  # Buffer to accumulate the chunks
+
+
+    for content in r.iter_content(100):
+        # Decode the byte content to a string
+        buffer += content.decode('utf-8')
+    return json.loads(buffer.split('data:')[len(buffer.split('data:'))-2])["output"]["data"][0]['label']
+
+def check_nsfw3(img_url):
+    data = {
+        'data': [
+            {'path': img_url}
+            ]
+
+        }
+    r = requests.post('https://zanderlewis-xl-nsfw-detection.hf.space/call/predict',json=data)
+    json_data = r.json()
+    event_id = json_data['event_id']
+    r = requests.get(f'https://zanderlewis-xl-nsfw-detection.hf.space/call/predict/{event_id}', stream=True)
+    event_stream = ''
+    for chunk in r.iter_content(100):
+        event_stream += chunk.decode('utf-8')
+    return ast.literal_eval(event_stream.split('data:')[-1])[0]['label']
+
+def get_replica_code(url):
+    try:
+        r = requests.get(url)
+
+        return r.text.split('replicas/')[1].split('"};')[0]
+    except:
+        return None
+def check_nsfw4(img_url):
+    code = get_replica_code('https://error466-falconsai-nsfw-image-detection.hf.space')
+    session_hash = ''.join(random.choice(string.ascii_lowercase + string.digits) for _ in range(7))
+    data = {
+        'data': [
+            {'path': img_url}
+            ],
+        'session_hash': session_hash,
+        'fn_index': 0,
+        'trigger_id': 58
+        }
+    r = requests.post(f'https://error466-falconsai-nsfw-image-detection.hf.space/--replicas/{code}/queue/join', json=data)
+
+    r = requests.get(f'https://error466-falconsai-nsfw-image-detection.hf.space/--replicas/{code}/queue/data?session_hash={session_hash}', stream=True)
+    buffer = ""  # Buffer to accumulate the chunks
+
+
+    for content in r.iter_content(100):
+        # Decode the byte content to a string
+        buffer += content.decode('utf-8')
+    return json.loads(buffer.split('data:')[-1])["output"]["data"][0]['label']
+
+def check_nsfw5(img_url):
+    session_hash = ''.join(random.choice(string.ascii_lowercase + string.digits) for _ in range(7))
+    data = {
+        'data': [
+            {'path': img_url}
+            ],
+        'session_hash': session_hash,
+        'fn_index': 0,
+        'trigger_id': 9
+        }
+    r = requests.post('https://phelpsgg-falconsai-nsfw-image-detection.hf.space/queue/join', json=data)
+
+    r = requests.get(f'https://phelpsgg-falconsai-nsfw-image-detection.hf.space/queue/data?session_hash={session_hash}', stream=True)
+    buffer = ""  # Buffer to accumulate the chunks
+
+
+    for content in r.iter_content(100):
+        # Decode the byte content to a string
+        buffer += content.decode('utf-8')
+    return json.loads(buffer.split('data:')[-1])["output"]["data"][0]['label']
+
+def check_nsfw_final(img_url):
+    result = None
+
+    try:
+        check = check_nsfw2(img_url)
+        if check == 'nsfw':
+            result = True
+        else:
+            result = False
+    except:
+        pass
+
+    if result is None:
+        try:
+            check = check_nsfw3(img_url)
+            if check == 'nsfw':
+                result = True
+            else:
+                result = False
+        except:
+            pass
+
+    if result is None:
+        try:
+            check = check_nsfw4(img_url)
+            if check == 'nsfw':
+                result = True
+            else:
+                result = False
+        except:
+            pass
+
+    if result is None:
+        try:
+            check = check_nsfw5(img_url)
+            if check == 'nsfw':
+                result = True
+            else:
+                result = False
+        except:
+            pass
+
+    return result
+
+
+def extract_frames(video_path, num_frames):
+    vidcap = cv2.VideoCapture(video_path)
+    total_frames = int(vidcap.get(cv2.CAP_PROP_FRAME_COUNT))
+    frames = []
+    
+    for i in range(num_frames):
+        frame_number = int(i * total_frames / num_frames)  # Sample evenly
+        vidcap.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
+        success, image = vidcap.read()
+        if success:
+            # Save frame to temporary file and append it to list
+            temp_img = tempfile.NamedTemporaryFile(suffix=".jpg", delete=False)
+            cv2.imwrite(temp_img.name, image)
+            frames.append(temp_img.name)
+        else:
+            break
+
+    vidcap.release()
+    return frames
+
+# Gradio app logic
+def process_video(video, num_frames):
+    video_path = os.path.join(tempfile.gettempdir(), video.name)
+    with open(video_path, "wb") as f:
+        f.write(video.read())
+    
+    frames = extract_frames(video_path, num_frames)
+    
+    nsfw_count = 0
+    total_frames = len(frames)
+
+    for frame_path in frames:
+        if check_nsfw_final(frame_path):
+            nsfw_count += 1
+        os.remove(frame_path) 
+
+    return f"{nsfw_count} out of {total_frames} frames were NSFW."
+
+with gr.Blocks() as app:
+    gr.Markdown("## NSFW Frame Detection in Video")
+
+    with gr.Row():
+        video_input = gr.Video(label="Upload Video")
+        num_frames_input = gr.Number(label="Number of Frames to Check", value=10, precision=0)
+
+    output_text = gr.Textbox(label="Result")
+
+    submit_button = gr.Button("Submit")
+    
+    submit_button.click(
+        fn=process_video,
+        inputs=[video_input, num_frames_input],
+        outputs=output_text
+    )
+
+app.launch()